Three-dimensional data creation method, client device, and server

ABSTRACT

A three-dimensional data creation method in a client device includes: creating three-dimensional data of a surrounding area of the client device using sensor information that is obtained through a sensor equipped in the client device and indicates a surrounding condition of the client device; estimating a self-location of the client device using the three-dimensional data created; and transmitting the sensor information obtained to a server or an other client device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. continuation application of PCT InternationalPatent Application Number PCT/JP2018/035230 filed on Sep. 21, 2018,claiming the benefit of priority of U.S. Provisional Patent ApplicationNo. 62/565,245 filed on Sep. 29, 2017, the entire contents of which arehereby incorporated by reference.

BACKGROUND 1. Technical Field

The present disclosure relates to a three-dimensional data creationmethod, a client device, and a server.

2. Description of the Related Art

Devices or services utilizing three-dimensional data are expected tofind their widespread use in a wide range of fields, such as computervision that enables autonomous operations of cars or robots, mapinformation, monitoring, infrastructure inspection, and videodistribution. Three-dimensional data is obtained through various meansincluding a distance sensor such as a rangefinder, as well as a stereocamera and a combination of a plurality of monocular cameras.

Methods of representing three-dimensional data include a method known asa point cloud scheme that represents the shape of a three-dimensionalstructure by a point group in a three-dimensional space. In the pointcloud scheme, the positions and colors of a point group are stored.While point cloud is expected to be a mainstream method of representingthree-dimensional data, a massive amount of data of a point groupnecessitates compression of the amount of three-dimensional data byencoding for accumulation and transmission, as in the case of atwo-dimensional moving picture (examples include MPEG-4 AVC and HEVCstandardized by MPEG).

Meanwhile, point cloud compression is partially supported by, forexample, an open-source library (Point Cloud Library) for pointcloud-related processing.

Furthermore, a technique for searching for and displaying a facilitylocated in the surroundings of the vehicle is known (for example, seeInternational Publication No. WO2014/020663).

SUMMARY

In such a three-dimensional data creation method for creatingthree-dimensional data, being able to reduce an amount of data to betransmitted and simplify a structure of a device is desired.

The present disclosure has an object to provide a three-dimensional datacreation method, a client device, and a server that are capable ofreducing an amount of data to be transmitted or simplifying a structureof a device.

A three-dimensional data creation method in a client device according toan aspect of the present disclosure includes: creating three-dimensionaldata of a surrounding area of the client device using sensor informationthat is obtained through a sensor equipped in the client device andindicates a surrounding condition of the client device; estimating aself-location of the client device using the three-dimensional datacreated; and transmitting the sensor information obtained to a server oran other client device.

A three-dimensional data creation method in a server that is capable ofcommunicating with a client device according to the present disclosureincludes: receiving sensor information from the client device that isobtained through a sensor equipped in the client device and indicates asurrounding condition of the client device; and creatingthree-dimensional data of a surrounding area of the client device usingthe sensor information received.

The present disclosure can provide a three-dimensional data creationmethod, a client device, and a server that are capable of reducing anamount of data to be transmitted or simplifying a structure of a device.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a diagram showing the structure of encoded three-dimensionaldata according to Embodiment 1;

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS according to Embodiment1;

FIG. 3 is a diagram showing an example of prediction structures amonglayers according to Embodiment 1;

FIG. 4 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1;

FIG. 5 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1;

FIG. 6 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 1;

FIG. 7 is a flowchart of encoding processes according to Embodiment 1;

FIG. 8 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 1;

FIG. 9 is a flowchart of decoding processes according to Embodiment 1;

FIG. 10 is a diagram showing an example of meta information according toEmbodiment 1;

FIG. 11 is a diagram showing an example structure of a SWLD according toEmbodiment 2;

FIG. 12 is a diagram showing example operations performed by a serverand a client according to Embodiment 2;

FIG. 13 is a diagram showing example operations performed by the serverand a client according to Embodiment 2;

FIG. 14 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2;

FIG. 15 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2;

FIG. 16 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 2;

FIG. 17 is a flowchart of encoding processes according to Embodiment 2;

FIG. 18 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 2;

FIG. 19 is a flowchart of decoding processes according to Embodiment 2;

FIG. 20 is a diagram showing an example structure of a WLD according toEmbodiment 2;

FIG. 21 is a diagram showing an example octree structure of the WLDaccording to Embodiment 2;

FIG. 22 is a diagram showing an example structure of a SWLD according toEmbodiment 2;

FIG. 23 is a diagram showing an example octree structure of the SWLDaccording to Embodiment 2;

FIG. 24 is a schematic diagram showing three-dimensional data beingtransmitted/received between vehicles according to Embodiment 3;

FIG. 25 is a diagram showing an example of three-dimensional datatransmitted between vehicles according to Embodiment 3;

FIG. 26 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 3;

FIG. 27 is a flowchart of the processes of creating three-dimensionaldata according to Embodiment 3;

FIG. 28 is a block diagram of a three-dimensional data transmissiondevice according to Embodiment 3;

FIG. 29 is a flowchart of the processes of transmittingthree-dimensional data according to Embodiment 3;

FIG. 30 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 3;

FIG. 31 is a flowchart of the processes of creating three-dimensionaldata according to Embodiment 3;

FIG. 32 is a block diagram of a three-dimensional data transmissiondevice according to Embodiment 3;

FIG. 33 is a flowchart of the processes of transmittingthree-dimensional data according to Embodiment 3;

FIG. 34 is a block diagram of a three-dimensional information processingdevice according to Embodiment 4;

FIG. 35 is a flowchart of a three-dimensional information processingmethod according to Embodiment 4;

FIG. 36 is a flowchart of a three-dimensional information processingmethod according to Embodiment 4;

FIG. 37 is a diagram that illustrates processes of transmittingthree-dimensional data according to Embodiment 5;

FIG. 38 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 5;

FIG. 39 is a flowchart of a three-dimensional data creation methodaccording to Embodiment 5;

FIG. 40 is a flowchart of a three-dimensional data creation methodaccording to Embodiment 5;

FIG. 41 is a flowchart of a display method according to Embodiment 6;

FIG. 42 is a diagram that illustrates an example of a surroundingenvironment visible through a windshield according to Embodiment 6;

FIG. 43 is a diagram that illustrates an example of a display on ahead-up display according to Embodiment 6;

FIG. 44 is a diagram that illustrates an example of a display on ahead-up display after adjustment according to Embodiment 6;

FIG. 45 is a diagram showing a structure of a system according toEmbodiment 7;

FIG. 46 is a block diagram of a client device according to Embodiment 7;

FIG. 47 is a block diagram of a server according to Embodiment 7;

FIG. 48 is a flowchart of a three-dimensional data creation processperformed by the client device according to Embodiment 7;

FIG. 49 is a flowchart of a sensor information transmission processperformed by the client device according to Embodiment 7;

FIG. 50 is a flowchart of a three-dimensional data creation processperformed by the server according to Embodiment 7;

FIG. 51 is a flowchart of a three-dimensional map transmission processperformed by the server according to Embodiment 7;

FIG. 52 is a diagram showing a structure of a variation of the systemaccording to Embodiment 7; and

FIG. 53 is a diagram showing a structure of the server and clientdevices according to Embodiment 7.

DETAILED DESCRIPTION OF THE EMBODIMENTS

While the use of encoded data such as that of a point cloud in an actualdevice or service requires random access to a desired spatial positionor object, there has been no functionality for random access in encodedthree-dimensional data, nor an encoding method therefor.

The present disclosure describes a three-dimensional data encodingmethod, a three-dimensional data decoding method, a three-dimensionaldata encoding device, or a three-dimensional data decoding devicecapable of providing random access functionality for encodedthree-dimensional data.

The three-dimensional data encoding method according to one aspect ofthe present disclosure is a three-dimensional data encoding method forencoding three-dimensional data, the method including: dividing thethree-dimensional data into first processing units, each being a randomaccess unit and being associated with three-dimensional coordinates; andencoding each of the first processing units to generate encoded data.

This enables random access on a first processing unit basis. Thethree-dimensional data encoding method is thus capable of providingrandom access functionality for encoded three-dimensional data.

For example, the three-dimensional data encoding method may includegenerating first information indicating the first processing units andthe three-dimensional coordinates associated with each of the firstprocessing units, and the encoded data may include the firstinformation.

For example, the first information may further indicate at least one ofan object, a time, and a data storage location that are associated witheach of the first processing units.

For example, in the dividing, each of the first processing units may befurther divided into second processing units, and in the encoding, eachof the second processing units may be encoded.

For example, in the encoding, a current second processing unit among thesecond processing units included in a current first processing unitamong the first processing units may be encoded by referring to anotherof the second processing units included in the current first processingunit.

With this, the encoding efficiency is increased by referring to anothersecond processing unit.

For example, in the encoding, one of three types may be selected as atype of the current second processing unit, and the current secondprocessing unit may be encoded in accordance with the type that has beenselected, the three types being a first type in which another of thesecond processing units is not referred to, a second type in whichanother of the second processing units is referred to, and a third typein which other two of the second processing units are referred to.

For example, in the encoding, a frequency of selecting the first typemay be changed in accordance with the number, or sparseness anddenseness of objects included in the three-dimensional data.

This enables an adequate setting of random accessibility and encodingefficiency, which are in a tradeoff relationship.

For example, in the encoding, a size of the first processing units maybe determined in accordance with the number, or sparseness and densenessof objects or dynamic objects included in the three-dimensional data.

This enables an adequate setting of random accessibility and encodingefficiency, which are in a tradeoff relationship.

For example, each of the first processing units may be spatially dividedin a predetermined direction to have layers, each including at least oneof the second processing units, and in the encoding, each of the secondprocessing units may be encoded by referring to another of the secondprocessing units included in an identical layer of the each of thesecond processing units or included in a lower layer of the identicallayer.

This achieves an increased random accessibility to an important layer ina system, while preventing a decrease in the encoding efficiency.

For example, in the dividing, among the second processing units, asecond processing unit including only a static object and a secondprocessing unit including only a dynamic object may be assigned todifferent ones of the first processing units.

This enables easy control of dynamic objects and static objects.

For example, in the encoding, dynamic objects may be individuallyencoded, and encoded data of each of the dynamic objects may beassociated with a second processing unit, among the second processingunits, that includes only a static object.

This enables easy control of dynamic objects and static objects.

For example, in the dividing, each of the second processing units may befurther divided into third processing units, and in the encoding, eachof the third processing units may be encoded.

For example, each of the third processing units may include at least onevoxel, which is a minimum unit in which position information isassociated. For example, each of the second processing units may includea keypoint group derived from information obtained by a sensor.

For example, the encoded data may include information indicating anencoding order of the first processing units.

For example, the encoded data may include information indicating a sizeof the first processing units.

For example, in the encoding, the first processing units may be encodedin parallel.

Also, the three-dimensional data decoding method according anotheraspect of the present disclosure is a three-dimensional data decodingmethod for decoding three-dimensional data, the method including:decoding each encoded data of first processing units, each being arandom access unit and being associated with three-dimensionalcoordinates, to generate three-dimensional data of the first processingunits.

This enables random access on a first processing unit basis. Thethree-dimensional data decoding method is thus capable of providingrandom access functionality for encoded three-dimensional data.

Also, the three-dimensional data encoding device according to stillanother aspect of the present disclosure is a three-dimensional dataencoding device that encodes three-dimensional data that may include: adivider that divides the three-dimensional data into first processingunits, each being a random access unit and being associated withthree-dimensional coordinates; and an encoder that encodes each of thefirst processing units to generate encoded data.

This enables random access on a first processing unit basis. Thethree-dimensional data encoding device is thus capable of providingrandom access functionality for encoded three-dimensional data.

Also, the three-dimensional data decoding device according to stillanother aspect of the present disclosure is a three-dimensional datadecoding device that decodes three-dimensional data that may include: adecoder that decodes each encoded data of first processing units, eachbeing a random access unit and being associated with three-dimensionalcoordinates, to generate three-dimensional data of the first processingunits.

This enables random access on a first processing unit basis. Thethree-dimensional data decoding device is thus capable of providingrandom access functionality for encoded three-dimensional data.

Note that the present disclosure, which is configured to divide a spacefor encoding, enables quantization, prediction, etc. of such space, andthus is effective also for the case where no random access is performed.

Also, the three-dimensional data encoding method according to one aspectof the present disclosure includes: extracting, from firstthree-dimensional data, second three-dimensional data having an amountof a feature greater than or equal to a threshold; and encoding thesecond three-dimensional data to generate first encodedthree-dimensional data.

According to this three-dimensional data encoding method, first encodedthree-dimensional data is generated that is obtained by encoding datahaving an amount of a feature greater than or equal to the threshold.This reduces the amount of encoded three-dimensional data compared tothe case where the first three-dimensional data is encoded as it is. Thethree-dimensional data encoding method is thus capable of reducing theamount of data to be transmitted.

For example, the three-dimensional data encoding method may furtherinclude encoding the first three-dimensional data to generate secondencoded three-dimensional data.

This three-dimensional data encoding method enables selectivetransmission of the first encoded three-dimensional data and the secondencoded three-dimensional data, in accordance, for example, with theintended use, etc. For example, the second three-dimensional data may beencoded by a first encoding method, and the first three-dimensional datamay be encoded by a second encoding method different from the firstencoding method.

This three-dimensional data encoding method enables the use of anencoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

For example, of intra prediction and inter prediction, the interprediction may be more preferentially performed in the first encodingmethod than in the second encoding method.

This three-dimensional data encoding method enables inter prediction tobe more preferentially performed on the second three-dimensional data inwhich adjacent data items are likely to have low correlation.

For example, the first encoding method and the second encoding methodmay represent three-dimensional positions differently.

This three-dimensional data encoding method enables the use of a moresuitable method to represent three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items included.

For example, at least one of the first encoded three-dimensional dataand the second encoded three-dimensional data may include an identifierindicating whether the at least one of the first encodedthree-dimensional data and the second encoded three-dimensional data isencoded three-dimensional data obtained by encoding the firstthree-dimensional data or encoded three-dimensional data obtained byencoding part of the first three-dimensional data.

This enables the decoding device to readily judge whether the obtainedencoded three-dimensional data is the first encoded three-dimensionaldata or the second encoded three-dimensional data.

For example, in the encoding of the second three-dimensional data, thesecond three-dimensional data may be encoded in a manner that the firstencoded three-dimensional data has a smaller data amount than a dataamount of the second encoded three-dimensional data.

This three-dimensional data encoding method enables the first encodedthree-dimensional data to have a smaller data amount than the dataamount of the second encoded three-dimensional data.

For example, in the extracting, data corresponding to an object having apredetermined attribute may be further extracted from the firstthree-dimensional data as the second three-dimensional data.

This three-dimensional data encoding method is capable of generating thefirst encoded three-dimensional data that includes data required by thedecoding device.

For example, the three-dimensional data encoding method may furtherinclude sending, to a client, one of the first encoded three-dimensionaldata and the second encoded three-dimensional data in accordance with astatus of the client.

This three-dimensional data encoding method is capable of sendingappropriate data in accordance with the status of the client.

For example, the status of the client may include one of a communicationcondition of the client and a traveling speed of the client.

For example, the three-dimensional data encoding method may furtherinclude sending, to a client, one of the first encoded three-dimensionaldata and the second encoded three-dimensional data in accordance with arequest from the client.

This three-dimensional data encoding method is capable of sendingappropriate data in accordance with the request from the client.

Also, the three-dimensional data decoding method according to anotheraspect of the present disclosure includes: decoding, by a first decodingmethod, first encoded three-dimensional data obtained by encoding secondthree-dimensional data having an amount of a feature greater than orequal to a threshold, the second three-dimensional data having beenextracted from first three-dimensional data; and decoding, by a seconddecoding method, second encoded three-dimensional data obtained byencoding the first three-dimensional data, the second decoding methodbeing different from the first decoding method.

This three-dimensional data decoding method enables selective receptionof the first encoded three-dimensional data obtained by encoding datahaving an amount of a feature greater than or equal to the threshold andthe second encoded three-dimensional data, in accordance, for example,with the intended use, etc. The three-dimensional data decoding methodis thus capable of reducing the amount of data to be transmitted. Suchthree-dimensional data decoding method further enables the use of adecoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

For example, of intra prediction and inter prediction, the interprediction may be more preferentially performed in the first decodingmethod than in the second decoding method.

This three-dimensional data decoding method enables inter prediction tobe more preferentially performed on the second three-dimensional data inwhich adjacent data items are likely to have low correlation.

For example, the first decoding method and the second decoding methodmay represent three-dimensional positions differently.

This three-dimensional data decoding method enables the use of a moresuitable method to represent three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items included.

For example, at least one of the first encoded three-dimensional dataand the second encoded three-dimensional data may include an identifierindicating whether the at least one of the first encodedthree-dimensional data and the second encoded three-dimensional data isencoded three-dimensional data obtained by encoding the firstthree-dimensional data or encoded three-dimensional data obtained byencoding part of the first three-dimensional data, and the identifiermay be referred to in identifying between the first encodedthree-dimensional data and the second encoded three-dimensional data.

This enables judgment to be readily made of whether the obtained encodedthree-dimensional data is the first encoded three-dimensional data orthe second encoded three-dimensional data.

For example, the three-dimensional data decoding method may furtherinclude: notifying a server of a status of a client; and receiving oneof the first encoded three-dimensional data and the second encodedthree-dimensional data from the server, in accordance with the status ofthe client.

This three-dimensional data decoding method is capable of receivingappropriate data in accordance with the status of the client.

For example, the status of the client may include one of a communicationcondition of the client and a traveling speed of the client.

For example, the three-dimensional data decoding method may furtherinclude: making a request of a server for one of the first encodedthree-dimensional data and the second encoded three-dimensional data;and receiving one of the first encoded three-dimensional data and thesecond encoded three-dimensional data from the server, in accordancewith the request.

This three-dimensional data decoding method is capable of receivingappropriate data in accordance with the intended use.

Also, the three-dimensional data encoding device according to stillanother aspect of the present disclosure include: an extractor thatextracts, from first three-dimensional data, second three-dimensionaldata having an amount of a feature greater than or equal to a threshold;and a first encoder that encodes the second three-dimensional data togenerate first encoded three-dimensional data.

This three-dimensional data encoding device generates first encodedthree-dimensional data by encoding data having an amount of a featuregreater than or equal to the threshold. This reduces the amount datacompared to the case where the first three-dimensional data is encodedas it is. The three-dimensional data encoding device is thus capable ofreducing the amount of data to be transmitted.

Also, the three-dimensional data decoding device according to stillanother aspect of the present disclosure includes: a first decoder thatdecodes, by a first decoding method, first encoded three-dimensionaldata obtained by encoding second three-dimensional data having an amountof a feature greater than or equal to a threshold, the secondthree-dimensional data having been extracted from firstthree-dimensional data; and a second decoder that decodes, by a seconddecoding method, second encoded three-dimensional data obtained byencoding the first three-dimensional data, the second decoding methodbeing different from the first decoding method.

This three-dimensional data decoding devices enables selective receptionof the first encoded three-dimensional data obtained by encoding datahaving an amount of a feature greater than or equal to the threshold andthe second encoded three-dimensional data, in accordance, for example,with the intended use, etc. The three-dimensional data decoding deviceis thus capable of reducing the amount of data to be transmitted. Suchthree-dimensional data decoding device further enables the use of adecoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

Also, the three-dimensional data creation method according to one aspectof the present disclosure includes: creating first three-dimensionaldata from information detected by a sensor; receiving encodedthree-dimensional data that is obtained by encoding secondthree-dimensional data; decoding the encoded three-dimensional data thathas been received to obtain the second three-dimensional data; andmerging the first three-dimensional data with the secondthree-dimensional data to create third three-dimensional data.

Such three-dimensional data creation method is capable of creatingdetailed three-dimensional data by use of the created firstthree-dimensional data and the received second three-dimensional data.

For example, in the merging, the first three-dimensional data may bemerged with the second three-dimensional data to create the thirdthree-dimensional data that is denser than the first three-dimensionaldata and the second three-dimensional data.

For example, the second three-dimensional data may be three-dimensionaldata that is generated by extracting, from fourth three-dimensionaldata, data having an amount of a feature greater than or equal to athreshold.

Such three-dimensional data creation method reduces the amount ofthree-dimensional data to be transmitted.

For example, the three-dimensional data creation method may furtherinclude searching for a transmission device that transmits the encodedthree-dimensional data, and in the receiving, the encodedthree-dimensional data may be received from the transmission device thathas been searched out.

Such three-dimensional data creation method is, for example, capable ofsearching for a transmission device having necessary three-dimensionaldata. For example, the three-dimensional data creation method mayfurther include: determining a request range that is a range of athree-dimensional space, three-dimensional data of which is requested;and transmitting information indicating the request range to thetransmission device, wherein the second three-dimensional data mayinclude the three-dimensional data of the request range.

Such three-dimensional data creation method is capable of receivingnecessary three-dimensional data, while reducing the amount ofthree-dimensional data to be transmitted.

For example, in the determining, a spatial range that includes anocclusion region undetectable by the sensor may be determined as therequest range.

The three-dimensional data transmission method according to anotheraspect of the present disclosure includes: creating fifththree-dimensional data from information detected by a sensor; extractingpart of the fifth three-dimensional data to create sixththree-dimensional data; encoding the sixth three-dimensional data togenerate encoded three-dimensional data; and transmitting the encodedthree-dimensional data.

Such three-dimensional data transmission method is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

For example, in the creating, the fifth three-dimensional data may becreated by creating seventh three-dimensional data from the informationdetected by the sensor, and by extracting data having an amount of afeature greater than or equal to a threshold from the sevenththree-dimensional data.

Such three-dimensional data transmission method reduces the amount ofthree-dimensional data to be transmitted.

For example, the three-dimensional data transmission method may furtherinclude: receiving, from a reception device, information indicating arequest range that is a range of a three-dimensional space,three-dimensional data of which is requested, wherein in the extracting,the sixth three-dimensional data may be created by extracting thethree-dimensional data of the request range from the fifththree-dimensional data, and in the transmitting, the encodedthree-dimensional data may be transmitted to the reception device.

Such three-dimensional data transmission method reduces the amount ofthree-dimensional data to be transmitted.

Also, the three-dimensional data creation device according to stillanother aspect of the present disclosure includes: a creator thatcreates first three-dimensional data from information detected by asensor; a receiver that receives encoded three-dimensional data that isobtained by encoding second three-dimensional data; a decoder thatdecodes the encoded three-dimensional data that has been received toobtain the second three-dimensional data; and a merger that merges thefirst three-dimensional data with the second three-dimensional data tocreate third three-dimensional data.

Such three-dimensional data creation device is capable of creatingdetailed third three-dimensional data by use of the created firstthree-dimensional data and the received second three-dimensional data.

Also, the three-dimensional data transmission device according to stillanother aspect of the present disclosure includes: a creator thatcreates fifth three-dimensional data from information detected by asensor; an extractor that extracts part of the fifth three-dimensionaldata to create sixth three-dimensional data; an encoder that encodes thesixth three-dimensional data to generate encoded three-dimensional data;and a transmitter that transmits the encoded three-dimensional data.

Such three-dimensional data transmission device is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

Also, the three-dimensional information processing method according oneaspect of the present disclosure includes: obtaining, via acommunication channel, map data that includes first three-dimensionalposition information; generating second three-dimensional positioninformation from information detected by a sensor; judging whether oneof the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present; determining a coping operation to cope with theabnormality when one of the first three-dimensional position informationand the second three-dimensional position information is judged to beabnormal; and executing a control that is required to perform the copingoperation.

Such three-dimensional information processing method is capable ofdetecting an abnormality regarding one of the first three-dimensionalposition information and the second three-dimensional positioninformation, and performing a coping operation therefor.

For example, the first three-dimensional position information mayinclude a plurality of random access units, each of which is an assemblyof at least one subspace and is individually decodable, the at least onesubspace having three-dimensional coordinates information and serving asa unit in which each of the plurality of random access units is encoded.

Such three-dimensional information processing method is capable ofreducing the data amount of the first three-dimensional positioninformation to be obtained.

For example, the first three-dimensional position information may bedata obtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.

Such three-dimensional information processing method is capable ofreducing the data amount of the first three-dimensional positioninformation to be obtained.

For example, the judging may include judging whether the firstthree-dimensional position information is obtainable via thecommunication channel, and when the first three-dimensional positioninformation is unobtainable via the communication channel, judging thefirst three-dimensional position information to be abnormal.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation in accordance withcommunication conditions, etc., when the first three-dimensionalposition information is unobtainable.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information. The judging mayinclude predicting whether the mobile object will enter an area in whichcommunication conditions are poor. In the executing of the control, themobile object may obtain the first three-dimensional positioninformation before entering the area in which the communicationconditions are poor, when the mobile object is predicted to enter thearea.

Such three-dimensional information processing method is capable ofobtaining the first three-dimensional position information in advance,when there is a possibility that the first three-dimensional positioninformation may be unobtainable.

For example, the executing of the control may include obtaining, via thecommunication channel, third three-dimensional position informationhaving a narrower range than a range of the first three-dimensionalposition information, when the first three-dimensional positioninformation is unobtainable via the communication channel.

Such three-dimensional information processing method is capable ofreducing the data amount of data to be obtained via a communicationchannel, thereby obtaining the three-dimensional position informationeven when communication conditions are poor.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information. The executing of thecontrol may include obtaining, via the communication channel, map dataincluding two-dimensional position information, when the firstthree-dimensional position information is unobtainable via thecommunication channel, and estimating the location of the mobile objecthaving the sensor by use of the two-dimensional position information andthe second three-dimensional position information.

Such three-dimensional information processing method is capable ofreducing the data amount of data to be obtained via a communicationchannel, thereby obtaining the three-dimensional position informationeven when communication conditions are poor.

For example, the three-dimensional information processing method mayfurther include: performing automatic operation of the mobile object byuse of the location having been estimated. The judging may furtherinclude judging whether to perform the automatic operation of the mobileobject by use of the location of the mobile object, based on anenvironment in which the mobile object is traveling, the location havingbeen estimated by use of the two-dimensional position information andthe second three-dimensional position information.

Such three-dimensional information processing method is capable ofjudging whether to continue automatic operation, in accordance with anenvironment in which the mobile object is traveling.

For example, the three-dimensional information processing method mayfurther include: performing automatic operation of the mobile object byuse of the location having been estimated. The executing of the controlmay include switching a mode of the automatic operation to another basedon an environment in which the mobile object is traveling.

Such three-dimensional information processing method is capable ofsetting an appropriate automatic operation mode, in accordance with anenvironment in which the mobile object is traveling.

For example, the judging may include judging whether the firstthree-dimensional position information has integrity, and when the firstthree-dimensional position information has no integrity, judging thefirst three-dimensional position information to be abnormal.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when, for example, the firstthree-dimensional position information is corrupt.

For example, the judging may include judging whether a data accuracy ishigher than or equal to a reference value, and when the data accuracy isnot higher than or equal to the reference value, judging the secondthree-dimensional position information to be abnormal, the data accuracybeing an accuracy of the second three-dimensional position informationhaving been generated.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when the accuracy of thesecond three-dimensional position information is low.

For example, the executing of the control may include generating fourththree-dimensional position information from information detected by analternative sensor different from the sensor, when the data accuracy ofthe second three-dimensional position information having been generatedis not higher than or equal to the reference value.

Such three-dimensional information processing method is capable ofobtaining three-dimensional position information by use of analternative sensor, when, for example, the sensor has trouble.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information; and performingautomatic operation of the mobile object by use of the location havingbeen estimated. The executing of the control may include switching amode of the automatic operation to another when the data accuracy of thesecond three-dimensional position information having been generated isnot higher than or equal to the reference value.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when the accuracy of thesecond three-dimensional position information is low.

For example, the executing of the control may include calibrating anoperation of the sensor, when the data accuracy of the secondthree-dimensional position information having been generated is nothigher than or equal to the reference value.

Such three-dimensional information processing method is capable ofincreasing the accuracy of the second three-dimensional positioninformation, when the accuracy of the second three-dimensional positioninformation is low.

Also, the three-dimensional information processing device according toanother aspect of the present disclosure includes: an obtainer thatobtains, via a communication channel, map data that includes firstthree-dimensional position information; a generator that generatessecond three-dimensional position information from information detectedby a sensor; a judgment unit that judges whether one of the firstthree-dimensional position information and the second three-dimensionalposition information is abnormal by performing, on one of the firstthree-dimensional position information and the second three-dimensionalposition information, a process of judging whether an abnormality ispresent; a determiner that determines a coping operation to cope withthe abnormality when one of the first three-dimensional positioninformation and the second three-dimensional position information isjudged to be abnormal; and an operation controller that executes acontrol required to perform the coping operation.

Such three-dimensional information processing device is capable ofdetecting an abnormality regarding one of the first three-dimensionalposition information and the second three-dimensional positioninformation, and performing a coping operation therefor.

Also, the three-dimensional data creation method according to one aspectof the present disclosure is a three-dimensional data creation methodfor use in a mobile object including a sensor and a communication unitthat transmits and receives three-dimensional data to and from anexternal device. This three-dimensional data creation method includes:creating second three-dimensional data based on information detected bythe sensor and first three-dimensional data received by thecommunication unit; and transmitting, to the external device, thirdthree-dimensional data that is part of the second three-dimensionaldata.

Such three-dimensional data creation method is capable of generatingthree-dimensional data of a range undetectable by the mobile object.Stated differently, such three-dimensional data creation method iscapable of generating detailed three-dimensional data. Thethree-dimensional data creation method is also capable of transmitting,to another mobile object, etc., three-dimensional data of a rangeundetectable by such another mobile object, etc.

For example, the creating and the transmitting may be repeatedlyperformed, and the third three-dimensional data may be three-dimensionaldata of a small space having a predetermined size and located apredetermined distance ahead of a current position of the mobile objectin a traveling direction of the mobile object.

This reduces the data amount of the third three-dimensional data to betransmitted.

For example, the predetermined distance may vary in accordance with atraveling speed of the mobile object.

Such three-dimensional data creation method is capable of setting anappropriate small space in accordance with the traveling speed of themobile object, and transmitting the three-dimensional data of such smallspace to another mobile object, etc.

For example, the predetermined size may vary in accordance with atraveling speed of the mobile object.

Such three-dimensional data creation method is capable of setting anappropriate small space in accordance with the traveling speed of themobile object, and transmitting the three-dimensional data of such smallspace to another mobile object, etc.

For example, the three-dimensional data creation method may furtherinclude: judging whether a change has occurred in the secondthree-dimensional data of the small space corresponding to the thirdthree-dimensional data already transmitted; and when the change hasoccurred, transmitting, to the external device, fourth three-dimensionaldata that is at least part of the second three-dimensional data in whichthe change has occurred.

Such three-dimensional data creation method is capable of transmitting,to another mobile object, etc., the fourth three-dimensional data of aspace in which a change has occurred.

For example, the fourth three-dimensional data may be morepreferentially transmitted than the third three-dimensional data.

Such three-dimensional data creation method preferentially transmits, toanother mobile object, etc., the fourth three-dimensional data of aspace in which a change has occurred, thereby enabling such anothermobile object, etc., to promptly make, for example, a judgment, etc.that is based on the three-dimensional data.

For example, when the change has occurred, the fourth three-dimensionaldata may be transmitted before the third three-dimensional data istransmitted.

For example, the fourth three-dimensional data may indicate a differencebetween the second three-dimensional data of the small spacecorresponding to the third three-dimensional data already transmittedand the second three-dimensional data that has undergone the change.

Such three-dimensional data creation method is capable of reducing theamount of the three-dimensional data to be transmitted.

For example, in the transmitting, the third three-dimensional data maynot be transmitted when no difference is present between the thirdthree-dimensional data of the small space and the firstthree-dimensional data of the small space.

This reduces the data amount of the third three-dimensional data to betransmitted.

For example, when no difference is present between the thirdthree-dimensional data of the small space and the firstthree-dimensional data of the small space, information may betransmitted to the external device, the information indicating that nodifference is present between the third three-dimensional data of thesmall space and the first three-dimensional data of the small space.

For example, the information detected by the sensor may bethree-dimensional data.

The three-dimensional data creation device according to another aspectof the present disclosure is a three-dimensional data creation deviceequipped in a mobile object. This three-dimensional data creation deviceincludes: a sensor; a receiver that receives first three-dimensionaldata from an external device; a creator that creates secondthree-dimensional data based on information detected by the sensor andthe first three-dimensional data; and a transmitter that transmits, tothe external device, third three-dimensional data that is part of thesecond three-dimensional data.

Such three-dimensional data creation device is capable of generatingthree-dimensional data of a range undetectable by the mobile object.Stated differently, such three-dimensional data creation device iscapable of generating detailed three-dimensional data. Thethree-dimensional data creation device is also capable of transmitting,to another mobile object, etc., three-dimensional data of a rangeundetectable by such another mobile object, etc.

Furthermore, a display method according to an aspect of the presentdisclosure is a display method performed by a display device thatoperates in conjunction with a mobile object, and includes: determiningwhich one of first surrounding information and second surroundinginformation is to be displayed, based on a driving condition of themobile object, the first surrounding information being information whichindicates a surrounding condition of the mobile object and is generatedusing two-dimensional information, the second surrounding informationbeing information which indicates the surrounding condition of themobile object and is generated using three-dimensional data; anddisplaying the one of the first surrounding information and the secondsurrounding information that is determined to be displayed.

Accordingly, in the display method, which between the first surroundinginformation generated using two-dimensional data and second surroundinginformation generated using three-dimensional data is to be displayedcan be switched based on the driving condition of the mobile object. Forexample, in the display method, the second surrounding information,which has a large amount of information, is displayed when detailedinformation is necessary, and the first surrounding information, whichhas a small amount of information, processing amount, and the like, isdisplayed when detailed information is not necessary. Accordingly, withthe display method, appropriate information can be displayed accordingto conditions, and the communication data amount, processing amount, andthe like, can be reduced.

For example, the driving condition may be whether the mobile object isunder autonomous travel or under manual driving, and in the determining,the first surrounding information may be determined to be displayed whenthe mobile object is under autonomous travel, and the second surroundinginformation may be determined to be displayed when the mobile object isunder manual driving.

Accordingly, detailed information can be displayed during manualdriving, and the processing amount during self-driving can be reduced.

For example, the driving condition may be an area in which the mobileobject is located.

Accordingly, appropriate information can be displayed according to thelocation of the mobile object.

For example, the three-dimensional data may be data obtained byextracting, from three-dimensional point cloud data, a point cloudhaving an amount of a feature greater than or equal to a threshold.

Accordingly, the communication data amount or the amount of data to bestored can be reduced.

For example, the three-dimensional data may be data having a meshstructure generated from three-dimensional point cloud data.

Accordingly, the communication data amount or the amount of data to bestored can be reduced.

For example, the three-dimensional data may be data obtained byextracting, from three-dimensional point cloud data, a point cloud whichhas an amount of a feature greater than or equal to a threshold and isnecessary for one of self-location estimation, drive assist, andself-driving.

Accordingly, the communication data amount or the amount of data to bestored can be reduced.

For example, the three-dimensional data may be three-dimensional pointcloud data.

Accordingly, the precision of the second surrounding information can beimproved.

For example, in the displaying, the second surrounding information maybe displayed on a head-up display, and the display method may furtherinclude adjusting a display position of the second surroundinginformation according to one of posture, physique, and eye position of auser aboard the mobile object.

Accordingly, information can be displayed at the appropriate positionaccording to the posture, physique or eye position of the user.

Furthermore, a display device according to an aspect of the presentdisclosure is a display device that operates in conjunction with amobile object, and includes: a determiner that determines which one offirst surrounding information and second surrounding information is tobe displayed, based on a driving condition of the mobile object, thefirst surrounding information being video which shows a surroundingcondition of the mobile object and is generated using two-dimensionalinformation, the second surrounding information being video which showsthe surrounding condition of the mobile object and is generated usingthree-dimensional data; and a display that displays the one of the firstsurrounding information and the second surrounding information that isdetermined to be displayed.

Accordingly, the display device can switch which between the firstsurrounding information generated using two-dimensional data and secondsurrounding information generated using three-dimensional data todisplay, based on the driving condition of the mobile object. Forexample, the display device displays the second surrounding information,which has a large amount of information, when detailed information isnecessary, and displays the first surrounding information, which has asmall amount of information, processing amount, and the like, whendetailed information is not necessary. Accordingly, the display deviceis capable of displaying appropriate information according to conditionsand reducing the communication data amount, the processing amount, andthe like.

A three-dimensional data creation method in a client device equipped ina mobile object according to an aspect of the present disclosureincludes: creating three-dimensional data of a surrounding area of themobile object using sensor information that is obtained through a sensorequipped in the mobile object and indicates a surrounding condition ofthe mobile object; estimating a self-location of the mobile object usingthe three-dimensional data created; and transmitting the sensorinformation obtained to a server or an other mobile object.

With this, the three-dimensional data creation method transmits thesensor information to the server and the like. This makes it possible tofurther reduce an amount of transmission data compared to whentransmitting the three-dimensional data. Since there is no need for theclient device to perform processes such as compressing or encoding thethree-dimensional data, it is possible to reduce a processing amount ofthe client device. As such, the three-dimensional data creation methodis capable of reducing the amount of data to be transmitted orsimplifying a structure of a device.

For example, three-dimensional data creation method may further transmita transmission request for a three-dimensional map to the server,receive the three-dimensional map from the server, and in the estimatingof the self-location, estimate the self-location using thethree-dimensional data and the three-dimensional map.

For example, the sensor information may include at least one ofinformation obtained by a laser sensor, a luminance image, an infraredimage, a depth image, sensor position information, or sensor speedinformation.

For example, the sensor information may include at least one ofinformation obtained by a laser sensor, a luminance image, an infraredimage, a depth image, sensor position information, or sensor speedinformation.

For example, the three-dimensional data creation method may encode orcompress the sensor information, and in the transmitting of the sensorinformation, transmit the sensor information that has been encoded orcompressed to the server or the other mobile object.

This enables the three-dimensional data creation method to reduce theamount of data to be transmitted.

A three-dimensional data creation method in a server that is capable ofcommunicating with a client device equipped in a mobile object accordingto the present disclosure includes: receiving sensor information fromthe client device that is obtained through a sensor equipped in themobile object and indicates a surrounding condition of the mobileobject; and creating three-dimensional data of a surrounding area of themobile object using the sensor information received.

With this, the three-dimensional data creation method createsthree-dimensional data using sensor information transmitted from aclient device. This makes it possible to further reduce the amount oftransmission data compared to when the client device transmits thethree-dimensional data. Since there is no need for the client device toperform processes such as compressing or encoding the three-dimensionaldata, it is possible to reduce the processing amount of the clientdevice. As such, the three-dimensional data creation method is capableof reducing the amount of data to be transmitted or simplifying thestructure of the device.

For example, the three-dimensional data creation method may furthertransmit a transmission request for the sensor information to the clientdevice. For example, the three-dimensional data creation method mayfurther update a three-dimensional map using the three-dimensional datacreated, and transmit the three-dimensional map to the client device inresponse to a transmission request for the three-dimensional map fromthe client device.

For example, the sensor information may include at least one ofinformation obtained by a laser sensor, a luminance image, an infraredimage, a depth image, sensor position information, or sensor speedinformation.

For example, the sensor information may include information thatindicates a performance of the sensor.

For example, the three-dimensional data creation method may furthercorrect the three-dimensional data in accordance with the performance ofthe sensor.

This enables the three-dimensional data creation method to improve thequality of the three-dimensional data.

For example, in the receiving of the sensor information, a plurality ofpieces of the sensor information may be received from a plurality ofclient devices each being the client device; and the sensor informationto be used in the creating of the three-dimensional data may beselected, based on a plurality of pieces of information that eachindicates the performance of the sensor included in the plurality ofpieces of the sensor information.

This enables the three-dimensional data creation method to improve thequality of the three-dimensional data.

For example, the sensor information received may be decoded ordecompressed; and the three-dimensional data may be created using thesensor information that has been decoded or decompressed.

This enables the three-dimensional data creation method to reduce theamount of data to be transmitted.

A client device equipped in a mobile object according to an aspect ofthe present disclosure includes a processor and memory. The processoruses the memory to: create three-dimensional data of a surrounding areaof the mobile object using sensor information that is obtained through asensor equipped in the mobile object and indicates a surroundingcondition of the mobile object; estimate a self-location of the mobileobject using the three-dimensional data created; and transmit the sensorinformation obtained to a server or an other mobile object.

With this, the client device transmits the sensor information to theserver and the like. This makes it possible to further reduce the amountof transmission data compared to when transmitting the three-dimensionaldata. Since there is no need for the client device to perform processessuch as compressing or encoding the three-dimensional data, it ispossible to reduce the processing amount of the client device. As such,the client device is capable of reducing the amount of data to betransmitted or simplifying the structure of the device.

A server that is capable of communicating with a client device equippedin a mobile object according to an aspect of the present disclosureincludes a processor and memory. The processor uses the memory to:receive sensor information from the client device that is obtainedthrough a sensor equipped in the mobile object and indicates asurrounding condition of the mobile object; and create three-dimensionaldata of a surrounding area of the mobile object using the sensorinformation received.

With this, the server creates the three-dimensional data using thesensor information transmitted from the client device. This makes itpossible to further reduce the amount of transmission data compared towhen the client device transmits the three-dimensional data. Since thereis no need for the client device to perform processes such ascompressing or encoding the three-dimensional data, it is possible toreduce the processing amount of the client device. As such, the serveris capable of reducing the amount of data to be transmitted orsimplifying the structure of the device.

Note that these general or specific aspects may be implemented as asystem, a method, an integrated circuit, a computer program, or acomputer-readable recording medium such as a CD-ROM, or may beimplemented as any combination of a system, a method, an integratedcircuit, a computer program, and a recording medium.

The following describes embodiments with reference to the drawings. Notethat the following embodiments show exemplary embodiments of the presentdisclosure. The numerical values, shapes, materials, structuralcomponents, the arrangement and connection of the structural components,steps, the processing order of the steps, etc. shown in the followingembodiments are mere examples, and thus are not intended to limit thepresent disclosure. Of the structural components described in thefollowing embodiments, structural components not recited in any one ofthe independent claims that indicate the broadest concepts will bedescribed as optional structural components.

Embodiment 1

First, the data structure of encoded three-dimensional data (hereinafteralso referred to as encoded data) according to the present embodimentwill be described. FIG. 1 is a diagram showing the structure of encodedthree-dimensional data according to the present embodiment.

In the present embodiment, a three-dimensional space is divided intospaces (SPCs), which correspond to pictures in moving picture encoding,and the three-dimensional data is encoded on a SPC-by-SPC basis. EachSPC is further divided into volumes (VLMs), which correspond tomacroblocks, etc. in moving picture encoding, and predictions andtransforms are performed on a VLM-by-VLM basis. Each volume includes aplurality of voxels (VXLs), each being a minimum unit in which positioncoordinates are associated. Note that prediction is a process ofgenerating predictive three-dimensional data analogous to a currentprocessing unit by referring to another processing unit, and encoding adifferential between the predictive three-dimensional data and thecurrent processing unit, as in the case of predictions performed ontwo-dimensional images. Such prediction includes not only spatialprediction in which another prediction unit corresponding to the sametime is referred to, but also temporal prediction in which a predictionunit corresponding to a different time is referred to.

When encoding a three-dimensional space represented by point group datasuch as a point cloud, for example, the three-dimensional data encodingdevice (hereinafter also referred to as the encoding device) encodes thepoints in the point group or points included in the respective voxels ina collective manner, in accordance with a voxel size. Finer voxelsenable a highly-precise representation of the three-dimensional shape ofa point group, while larger voxels enable a rough representation of thethree-dimensional shape of a point group.

Note that the following describes the case where three-dimensional datais a point cloud, but three-dimensional data is not limited to a pointcloud, and thus three-dimensional data of any format may be employed.

Also note that voxels with a hierarchical structure may be used. In sucha case, when the hierarchy includes n levels, whether a sampling pointis included in the n−1th level or its lower levels (the lower levels ofthe n-th level) may be sequentially indicated. For example, when onlythe n-th level is decoded, and the n−1th level or its lower levelsinclude a sampling point, the n-th level can be decoded on theassumption that a sampling point is included at the center of a voxel inthe n-th level.

Also, the encoding device obtains point group data, using, for example,a distance sensor, a stereo camera, a monocular camera, a gyroscopesensor, or an inertial sensor.

As in the case of moving picture encoding, each SPC is classified intoone of at least the three prediction structures that include: intra SPC(I-SPC), which is individually decodable; predictive SPC (P-SPC) capableof only a unidirectional reference; and bidirectional SPC (B-SPC)capable of bidirectional references. Each SPC includes two types of timeinformation: decoding time and display time.

Furthermore, as shown in FIG. 1, a processing unit that includes aplurality of SPCs is a group of spaces (GOS), which is a random accessunit. Also, a processing unit that includes a plurality of GOSs is aworld (WLD).

The spatial region occupied by each world is associated with an absoluteposition on earth, by use of, for example, GPS, or latitude andlongitude information. Such position information is stored asmeta-information. Note that meta-information may be included in encodeddata, or may be transmitted separately from the encoded data.

Also, inside a GOS, all SPCs may be three-dimensionally adjacent to oneanother, or there may be a SPC that is not three-dimensionally adjacentto another SPC.

Note that the following also describes processes such as encoding,decoding, and reference to be performed on three-dimensional dataincluded in processing units such as GOS, SPC, and VLM, simply asperforming encoding/to encode, decoding/to decode, referring to, etc. ona processing unit. Also note that three-dimensional data included in aprocessing unit includes, for example, at least one pair of a spatialposition such as three-dimensional coordinates and an attribute valuesuch as color information.

Next, the prediction structures among SPCs in a GOS will be described. Aplurality of SPCs in the same GOS or a plurality of VLMs in the same SPCoccupy mutually different spaces, while having the same time information(the decoding time and the display time).

A SPC in a GOS that comes first in the decoding order is an I-SPC. GOSscome in two types: closed GOS and open GOS. A closed GOS is a GOS inwhich all SPCs in the GOS are decodable when decoding starts from thefirst I-SPC. Meanwhile, an open GOS is a GOS in which a different GOS isreferred to in one or more SPCs preceding the first I-SPC in the GOS inthe display time, and thus cannot be singly decoded.

Note that in the case of encoded data of map information, for example, aWLD is sometimes decoded in the backward direction, which is opposite tothe encoding order, and thus backward reproduction is difficult whenGOSs are interdependent. In such a case, a closed GOS is basically used.

Each GOS has a layer structure in height direction, and SPCs aresequentially encoded or decoded from SPCs in the bottom layer.

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS. FIG. 3 is a diagramshowing an example of prediction structures among layers.

A GOS includes at least one I-SPC. Of the objects in a three-dimensionalspace, such as a person, an animal, a car, a bicycle, a signal, and abuilding serving as a landmark, a small-sized object is especiallyeffective when encoded as an I-SPC. When decoding a GOS at a lowthroughput or at a high speed, for example, the three-dimensional datadecoding device (hereinafter also referred to as the decoding device)decodes only I-SPC(s) in the GOS.

The encoding device may also change the encoding interval or theappearance frequency of I-SPCs, depending on the degree of sparsenessand denseness of the objects in a WLD.

In the structure shown in FIG. 3, the encoding device or the decodingdevice encodes or decodes a plurality of layers sequentially from thebottom layer (layer 1). This increases the priority of data on theground and its vicinity, which involve a larger amount of information,when, for example, a self-driving car is concerned.

Regarding encoded data used for a drone, for example, encoding ordecoding may be performed sequentially from SPCs in the top layer in aGOS in height direction.

The encoding device or the decoding device may also encode or decode aplurality of layers in a manner that the decoding device can have arough grasp of a GOS first, and then the resolution is graduallyincreased. The encoding device or the decoding device may performencoding or decoding in the order of layers 3, 8, 1, 9 . . . , forexample.

Next, the handling of static objects and dynamic objects will bedescribed.

A three-dimensional space includes scenes or still objects such as abuilding and a road (hereinafter collectively referred to as staticobjects), and objects with motion such as a car and a person(hereinafter collectively referred to as dynamic objects). Objectdetection is separately performed by, for example, extracting keypointsfrom point cloud data, or from video of a camera such as a stereocamera. In this description, an example method of encoding a dynamicobject will be described.

A first method is a method in which a static object and a dynamic objectare encoded without distinction. A second method is a method in which adistinction is made between a static object and a dynamic object on thebasis of identification information.

For example, a GOS is used as an identification unit. In such a case, adistinction is made between a GOS that includes SPCs constituting astatic object and a GOS that includes SPCs constituting a dynamicobject, on the basis of identification information stored in the encodeddata or stored separately from the encoded data.

Alternatively, a SPC may be used as an identification unit. In such acase, a distinction is made between a SPC that includes VLMsconstituting a static object and a SPC that includes VLMs constituting adynamic object, on the basis of the identification information thusdescribed.

Alternatively, a VLM or a VXL may be used as an identification unit. Insuch a case, a distinction is made between a VLM or a VXL that includesa static object and a VLM or a VXL that includes a dynamic object, onthe basis of the identification information thus described.

The encoding device may also encode a dynamic object as at least one VLMor SPC, and may encode a VLM or a SPC including a static object and aSPC including a dynamic object as mutually different GOSs. When the GOSsize is variable depending on the size of a dynamic object, the encodingdevice separately stores the GOS size as meta-information.

The encoding device may also encode a static object and a dynamic objectseparately from each other, and may superimpose the dynamic object ontoa world constituted by static objects. In such a case, the dynamicobject is constituted by at least one SPC, and each SPC is associatedwith at least one SPC constituting the static object onto which the eachSPC is to be superimposed. Note that a dynamic object may be representednot by SPC(s) but by at least one VLM or VXL.

The encoding device may also encode a static object and a dynamic objectas mutually different streams.

The encoding device may also generate a GOS that includes at least oneSPC constituting a dynamic object. The encoding device may further setthe size of a GOS including a dynamic object (GOS_M) and the size of aGOS including a static object corresponding to the spatial region ofGOS_M at the same size (such that the same spatial region is occupied).This enables superimposition to be performed on a GOS-by-GOS basis.

SPC(s) included in another encoded GOS may be referred to in a P-SPC ora B-SPC constituting a dynamic object. In the case where the position ofa dynamic object temporally changes, and the same dynamic object isencoded as an object in a GOS corresponding to a different time,referring to SPC(s) across GOSs is effective in terms of compressionrate.

The first method and the second method may be selected in accordancewith the intended use of encoded data. When encoded three-dimensionaldata is used as a map, for example, a dynamic object is desired to beseparated, and thus the encoding device uses the second method.Meanwhile, the encoding device uses the first method when the separationof a dynamic object is not required such as in the case wherethree-dimensional data of an event such as a concert and a sports eventis encoded.

The decoding time and the display time of a GOS or a SPC are storable inencoded data or as meta-information. All static objects may have thesame time information. In such a case, the decoding device may determinethe actual decoding time and display time. Alternatively, a differentvalue may be assigned to each GOS or SPC as the decoding time, and thesame value may be assigned as the display time. Furthermore, as in thecase of the decoder model in moving picture encoding such asHypothetical Reference Decoder (HRD) compliant with HEVC, a model may beemployed that ensures that a decoder can perform decoding without failby having a buffer of a predetermined size and by reading a bitstream ata predetermined bit rate in accordance with the decoding times.

Next, the topology of GOSs in a world will be described. The coordinatesof the three-dimensional space in a world are represented by the threecoordinate axes (x axis, y axis, and z axis) that are orthogonal to oneanother. A predetermined rule set for the encoding order of GOSs enablesencoding to be performed such that spatially adjacent GOSs arecontiguous in the encoded data. In an example shown in FIG. 4, forexample, GOSs in the x and z planes are successively encoded. After thecompletion of encoding all GOSs in certain x and z planes, the value ofthe y axis is updated. Stated differently, the world expands in the yaxis direction as the encoding progresses. The GOS index numbers are setin accordance with the encoding order.

Here, the three-dimensional spaces in the respective worlds arepreviously associated one-to-one with absolute geographical coordinatessuch as GPS coordinates or latitude/longitude coordinates.Alternatively, each three-dimensional space may be represented as aposition relative to a previously set reference position. The directionsof the x axis, the y axis, and the z axis in the three-dimensional spaceare represented by directional vectors that are determined on the basisof the latitudes and the longitudes, etc. Such directional vectors arestored together with the encoded data as meta-information.

GOSs have a fixed size, and the encoding device stores such size asmeta-information. The GOS size may be changed depending on, for example,whether it is an urban area or not, or whether it is inside or outsideof a room. Stated differently, the GOS size may be changed in accordancewith the amount or the attributes of objects with information values.Alternatively, in the same world, the encoding device may adaptivelychange the GOS size or the interval between I-SPCs in GOSs in accordancewith the object density, etc. For example, the encoding device sets theGOS size to smaller and the interval between I-SPCs in GOSs to shorter,as the object density is higher.

In an example shown in FIG. 5, to enable random access with a finergranularity, a GOS with a high object density is partitioned into theregions of the third to tenth GOSs. Note that the seventh to tenth GOSsare located behind the third to sixth GOSs.

Next, the structure and the operation flow of the three-dimensional dataencoding device according to the present embodiment will be described.FIG. 6 is a block diagram of three-dimensional data encoding device 100according to the present embodiment. FIG. 7 is a flowchart of an exampleoperation performed by three-dimensional data encoding device 100.

Three-dimensional data encoding device 100 shown in FIG. 6 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. Such three-dimensional data encoding device 100 includesobtainer 101, encoding region determiner 102, divider 103, and encoder104.

As shown in FIG. 7, first, obtainer 101 obtains three-dimensional data111, which is point group data (S101).

Next, encoding region determiner 102 determines a current region forencoding from among spatial regions corresponding to the obtained pointgroup data (S102). For example, in accordance with the position of auser or a vehicle, encoding region determiner 102 determines, as thecurrent region, a spatial region around such position.

Next, divider 103 divides the point group data included in the currentregion into processing units. The processing units here means units suchas GOSs and SPCs described above. The current region here correspondsto, for example, a world described above. More specifically, divider 103divides the point group data into processing units on the basis of apredetermined GOS size, or the presence/absence/size of a dynamic object(S103). Divider 103 further determines the starting position of the SPCthat comes first in the encoding order in each GOS.

Next, encoder 104 sequentially encodes a plurality of SPCs in each GOS,thereby generating encoded three-dimensional data 112 (S104).

Note that although an example is described here in which the currentregion is divided into GOSs and SPCs, after which each GOS is encoded,the processing steps are not limited to this order. For example, stepsmay be employed in which the structure of a single GOS is determined,which is followed by the encoding of such GOS, and then the structure ofthe subsequent GOS is determined.

As thus described, three-dimensional data encoding device 100 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. More specifically, three-dimensional data encoding device 100divides three-dimensional data into first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, divides each of the first processing units (GOSs) intosecond processing units (SPCs), and divides each of the secondprocessing units (SPCs) into third processing units (VLMs). Each of thethird processing units (VLMs) includes at least one voxel (VXL), whichis the minimum unit in which position information is associated.

Next, three-dimensional data encoding device 100 encodes each of thefirst processing units (GOSs), thereby generating encodedthree-dimensional data 112. More specifically, three-dimensional dataencoding device 100 encodes each of the second processing units (SPCs)in each of the first processing units (GOSs). Three-dimensional dataencoding device 100 further encodes each of the third processing units(VLMs) in each of the second processing units (SPCs).

When a current first processing unit (GOS) is a closed GOS, for example,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS). Stated differently,three-dimensional data encoding device 100 refers to no secondprocessing unit (SPC) included in a first processing unit (GOS) that isdifferent from the current first processing unit (GOS).

Meanwhile, when a current first processing unit (GOS) is an open GOS,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS) or a second processing unit(SPC) included in a first processing unit (GOS) that is different fromthe current first processing unit (GOS).

Also, three-dimensional data encoding device 100 selects, as the type ofa current second processing unit (SPC), one of the following: a firsttype (I-SPC) in which another second processing unit (SPC) is notreferred to; a second type (P-SPC) in which another single secondprocessing unit (SPC) is referred to; and a third type in which othertwo second processing units (SPC) are referred to. Three-dimensionaldata encoding device 100 encodes the current second processing unit(SPC) in accordance with the selected type.

Next, the structure and the operation flow of the three-dimensional datadecoding device according to the present embodiment will be described.FIG. 8 is a block diagram of three-dimensional data decoding device 200according to the present embodiment. FIG. 9 is a flowchart of an exampleoperation performed by three-dimensional data decoding device 200.

Three-dimensional data decoding device 200 shown in FIG. 8 decodesencoded three-dimensional data 211, thereby generating decodedthree-dimensional data 212. Encoded three-dimensional data 211 here is,for example, encoded three-dimensional data 112 generated bythree-dimensional data encoding device 100. Such three-dimensional datadecoding device 200 includes obtainer 201, decoding start GOS determiner202, decoding SPC determiner 203, and decoder 204.

First, obtainer 201 obtains encoded three-dimensional data 211 (S201).Next, decoding start GOS determiner 202 determines a current GOS fordecoding (S202). More specifically, decoding start GOS determiner 202refers to meta-information stored in encoded three-dimensional data 211or stored separately from the encoded three-dimensional data todetermine, as the current GOS, a GOS that includes a SPC correspondingto the spatial position, the object, or the time from which decoding isto start.

Next, decoding SPC determiner 203 determines the type(s) (I, P, and/orB) of SPCs to be decoded in the GOS (S203). For example, decoding SPCdeterminer 203 determines whether to (1) decode only I-SPC(s), (2) todecode I-SPC(s) and P-SPCs, or (3) to decode SPCs of all types. Notethat the present step may not be performed, when the type(s) of SPCs tobe decoded are previously determined such as when all SPCs arepreviously determined to be decoded.

Next, decoder 204 obtains an address location within encodedthree-dimensional data 211 from which a SPC that comes first in the GOSin the decoding order (the same as the encoding order) starts. Decoder204 obtains the encoded data of the first SPC from the address location,and sequentially decodes the SPCs from such first SPC (S204). Note thatthe address location is stored in the meta-information, etc.

Three-dimensional data decoding device 200 decodes decodedthree-dimensional data 212 as thus described. More specifically,three-dimensional data decoding device 200 decodes each encodedthree-dimensional data 211 of the first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, thereby generating decoded three-dimensional data 212 ofthe first processing units (GOSs). Even more specifically,three-dimensional data decoding device 200 decodes each of the secondprocessing units (SPCs) in each of the first processing units (GOSs).Three-dimensional data decoding device 200 further decodes each of thethird processing units (VLMs) in each of the second processing units(SPCs).

The following describes meta-information for random access. Suchmeta-information is generated by three-dimensional data encoding device100, and included in encoded three-dimensional data 112 (211).

In the conventional random access for a two-dimensional moving picture,decoding starts from the first frame in a random access unit that isclose to a specified time. Meanwhile, in addition to times, randomaccess to spaces (coordinates, objects, etc.) is assumed to be performedin a world.

To enable random access to at least three elements of coordinates,objects, and times, tables are prepared that associate the respectiveelements with the GOS index numbers. Furthermore, the GOS index numbersare associated with the addresses of the respective first I-SPCs in theGOSs. FIG. 10 is a diagram showing example tables included in themeta-information. Note that not all the tables shown in FIG. 10 arerequired to be used, and thus at least one of the tables is used.

The following describes an example in which random access is performedfrom coordinates as a starting point. To access the coordinates (x2, y2,and z2), the coordinates-GOS table is first referred to, which indicatesthat the point corresponding to the coordinates (x2, y2, and z2) isincluded in the second GOS. Next, the GOS-address table is referred to,which indicates that the address of the first I-SPC in the second GOS isaddr(2). As such, decoder 204 obtains data from this address to startdecoding.

Note that the addresses may either be logical addresses or physicaladdresses of an HDD or a memory. Alternatively, information thatidentifies file segments may be used instead of addresses. File segmentsare, for example, units obtained by segmenting at least one GOS, etc.

When an object spans across a plurality of GOSs, the object-GOS tablemay show a plurality of GOSs to which such object belongs. When suchplurality of GOSs are closed GOSs, the encoding device and the decodingdevice can perform encoding or decoding in parallel. Meanwhile, whensuch plurality of GOSs are open GOSs, a higher compression efficiency isachieved by the plurality of GOSs referring to each other.

Example objects include a person, an animal, a car, a bicycle, a signal,and a building serving as a landmark. For example, three-dimensionaldata encoding device 100 extracts keypoints specific to an object from athree-dimensional point cloud, etc., when encoding a world, and detectsthe object on the basis of such keypoints to set the detected object asa random access point.

As thus described, three-dimensional data encoding device 100 generatesfirst information indicating a plurality of first processing units(GOSs) and the three-dimensional coordinates associated with therespective first processing units (GOSs). Encoded three-dimensional data112 (211) includes such first information. The first information furtherindicates at least one of objects, times, and data storage locationsthat are associated with the respective first processing units (GOSs).

Three-dimensional data decoding device 200 obtains the first informationfrom encoded three-dimensional data 211. Using such first information,three-dimensional data decoding device 200 identifies encodedthree-dimensional data 211 of the first processing unit that correspondsto the specified three-dimensional coordinates, object, or time, anddecodes encoded three-dimensional data 211.

The following describes an example of other meta-information. Inaddition to the meta-information for random access, three-dimensionaldata encoding device 100 may also generate and store meta-information asdescribed below, and three-dimensional data decoding device 200 may usesuch meta-information at the time of decoding.

When three-dimensional data is used as map information, for example, aprofile is defined in accordance with the intended use, and informationindicating such profile may be included in meta-information. Forexample, a profile is defined for an urban or a suburban area, or for aflying object, and the maximum or minimum size, etc. of a world, a SPCor a VLM, etc. is defined in each profile. For example, more detailedinformation is required for an urban area than for a suburban area, andthus the minimum VLM size is set to small.

The meta-information may include tag values indicating object types.Each of such tag values is associated with VLMs, SPCs, or GOSs thatconstitute an object. For example, a tag value may be set for eachobject type in a manner, for example, that the tag value “0” indicates“person,” the tag value “1” indicates “car,” and the tag value “2”indicates “signal.” Alternatively, when an object type is hard to judge,or such judgment is not required, a tag value may be used that indicatesthe size or the attribute indicating, for example, whether an object isa dynamic object or a static object.

The meta-information may also include information indicating a range ofthe spatial region occupied by a world.

The meta-information may also store the SPC or V×L size as headerinformation common to the whole stream of the encoded data or to aplurality of SPCs, such as SPCs in a GOS.

The meta-information may also include identification information on adistance sensor or a camera that has been used to generate a pointcloud, or information indicating the positional accuracy of a pointgroup in the point cloud.

The meta-information may also include information indicating whether aworld is made only of static objects or includes a dynamic object.

The following describes variations of the present embodiment.

The encoding device or the decoding device may encode or decode two ormore mutually different SPCs or GOSs in parallel. GOSs to be encoded ordecoded in parallel can be determined on the basis of meta-information,etc. indicating the spatial positions of the GOSs.

When three-dimensional data is used as a spatial map for use by a car ora flying object, etc. in traveling, or for creation of such a spatialmap, for example, the encoding device or the decoding device may encodeor decode GOSs or SPCs included in a space that is identified on thebasis of GPS information, the route information, the zoom magnification,etc.

The decoding device may also start decoding sequentially from a spacethat is close to the self-location or the traveling route. The encodingdevice or the decoding device may give a lower priority to a spacedistant from the self-location or the traveling route than the priorityof a nearby space to encode or decode such distant place. To “give alower priority” means here, for example, to lower the priority in theprocessing sequence, to decrease the resolution (to apply decimation inthe processing), or to lower the image quality (to increase the encodingefficiency by, for example, setting the quantization step to larger).

When decoding encoded data that is hierarchically encoded in a space,the decoding device may decode only the bottom level in the hierarchy.

The decoding device may also start decoding preferentially from thebottom level of the hierarchy in accordance with the zoom magnificationor the intended use of the map.

For self-location estimation or object recognition, etc. involved in theself-driving of a car or a robot, the encoding device or the decodingdevice may encode or decode regions at a lower resolution, except for aregion that is lower than or at a specified height from the ground (theregion to be recognized). The encoding device may also encode pointclouds representing the spatial shapes of a room interior and a roomexterior separately. For example, the separation of a GOS representing aroom interior (interior GOS) and a GOS representing a room exterior(exterior GOS) enables the decoding device to select a GOS to be decodedin accordance with a viewpoint location, when using the encoded data.

The encoding device may also encode an interior GOS and an exterior GOShaving close coordinates so that such GOSs come adjacent to each otherin an encoded stream. For example, the encoding device associates theidentifiers of such GOSs with each other, and stores informationindicating the associated identifiers into the meta-information that isstored in the encoded stream or stored separately. This enables thedecoding device to refer to the information in the meta-information toidentify an interior GOS and an exterior GOS having close coordinates

The encoding device may also change the GOS size or the SPC sizedepending on whether a GOS is an interior GOS or an exterior GOS. Forexample, the encoding device sets the size of an interior GOS to smallerthan the size of an exterior GOS. The encoding device may also changethe accuracy of extracting keypoints from a point cloud, or the accuracyof detecting objects, for example, depending on whether a GOS is aninterior GOS or an exterior GOS. The encoding device may also add, toencoded data, information by which the decoding device displays objectswith a distinction between a dynamic object and a static object. Thisenables the decoding device to display a dynamic object together with,for example, a red box or letters for explanation. Note that thedecoding device may display only a red box or letters for explanation,instead of a dynamic object. The decoding device may also display moreparticular object types. For example, a red box may be used for a car,and a yellow box may be used for a person.

The encoding device or the decoding device may also determine whether toencode or decode a dynamic object and a static object as a different SPCor GOS, in accordance with, for example, the appearance frequency ofdynamic objects or a ratio between static objects and dynamic objects.For example, when the appearance frequency or the ratio of dynamicobjects exceeds a threshold, a SPC or a GOS including a mixture of adynamic object and a static object is accepted, while when theappearance frequency or the ratio of dynamic objects is below athreshold, a SPC or GOS including a mixture of a dynamic object and astatic object is unaccepted.

When detecting a dynamic object not from a point cloud but fromtwo-dimensional image information of a camera, the encoding device mayseparately obtain information for identifying a detection result (box orletters) and the object position, and encode these items of informationas part of the encoded three-dimensional data. In such a case, thedecoding device superimposes auxiliary information (box or letters)indicating the dynamic object onto a resultant of decoding a staticobject to display it.

The encoding device may also change the sparseness and denseness of VXLsor VLMs in a SPC in accordance with the degree of complexity of theshape of a static object. For example, the encoding device sets VXLs orVLMs at a higher density as the shape of a static object is morecomplex. The encoding device may further determine a quantization step,etc. for quantizing spatial positions or color information in accordancewith the sparseness and denseness of VXLs or VLMs. For example, theencoding device sets the quantization step to smaller as the density ofVXLs or VLMs is higher.

As described above, the encoding device or the decoding device accordingto the present embodiment encodes or decodes a space on a SPC-by-SPCbasis that includes coordinate information.

Furthermore, the encoding device and the decoding device performencoding or decoding on a volume-by-volume basis in a SPC. Each volumeincludes a voxel, which is the minimum unit in which positioninformation is associated.

Also, using a table that associates the respective elements of spatialinformation including coordinates, objects, and times with GOSs or usinga table that associates these elements with each other, the encodingdevice and the decoding device associate any ones of the elements witheach other to perform encoding or decoding. The decoding device uses thevalues of the selected elements to determine the coordinates, andidentifies a volume, a voxel, or a SPC from such coordinates to decode aSPC including such volume or voxel, or the identified SPC.

Furthermore, the encoding device determines a volume, a voxel, or a SPCthat is selectable in accordance with the elements, through extractionof keypoints and object recognition, and encodes the determined volume,voxel, or SPC, as a volume, a voxel, or a SPC to which random access ispossible.

SPCs are classified into three types: I-SPC that is singly encodable ordecodable; P-SPC that is encoded or decoded by referring to any one ofthe processed SPCs; and B-SPC that is encoded or decoded by referring toany two of the processed SPCs.

At least one volume corresponds to a static object or a dynamic object.A SPC including a static object and a SPC including a dynamic object areencoded or decoded as mutually different GOSs. Stated differently, a SPCincluding a static object and a SPC including a dynamic object areassigned to different GOSs.

Dynamic objects are encoded or decoded on an object-by-object basis, andare associated with at least one SPC including a static object. Stateddifferently, a plurality of dynamic objects are individually encoded,and the obtained encoded data of the dynamic objects is associated witha SPC including a static object.

The encoding device and the decoding device give an increased priorityto I-SPC(s) in a GOS to perform encoding or decoding. For example, theencoding device performs encoding in a manner that prevents thedegradation of I-SPCs (in a manner that enables the originalthree-dimensional data to be reproduced with a higher fidelity afterdecoded). The decoding device decodes, for example, only I-SPCs.

The encoding device may change the frequency of using I-SPCs dependingon the sparseness and denseness or the number (amount) of the objects ina world to perform encoding. Stated differently, the encoding devicechanges the frequency of selecting I-SPCs depending on the number or thesparseness and denseness of the objects included in thethree-dimensional data. For example, the encoding device uses I-SPCs ata higher frequency as the density of the objects in a world is higher.

The encoding device also sets random access points on a GOS-by-GOSbasis, and stores information indicating the spatial regionscorresponding to the GOSs into the header information.

The encoding devices uses, for example, a default value as the spatialsize of a GOS. Note that the encoding device may change the GOS sizedepending on the number (amount) or the sparseness and denseness ofobjects or dynamic objects. For example, the encoding device sets thespatial size of a GOS to smaller as the density of objects or dynamicobjects is higher or the number of objects or dynamic objects isgreater.

Also, each SPC or volume includes a keypoint group that is derived byuse of information obtained by a sensor such as a depth sensor, agyroscope sensor, or a camera sensor. The coordinates of the keypointsare set at the central positions of the respective voxels. Furthermore,finer voxels enable highly accurate position information.

The keypoint group is derived by use of a plurality of pictures. Aplurality of pictures include at least two types of time information:the actual time information and the same time information common to aplurality of pictures that are associated with SPCs (for example, theencoding time used for rate control, etc.).

Also, encoding or decoding is performed on a GOS-by-GOS basis thatincludes at least one SPC.

The encoding device and the decoding device predict P-SPCs or B-SPCs ina current GOS by referring to SPCs in a processed GOS.

Alternatively, the encoding device and the decoding device predictP-SPCs or B-SPCs in a current GOS, using the processed SPCs in thecurrent GOS, without referring to a different GOS.

Furthermore, the encoding device and the decoding device transmit orreceive an encoded stream on a world-by-world basis that includes atleast one GOS.

Also, a GOS has a layer structure in one direction at least in a world,and the encoding device and the decoding device start encoding ordecoding from the bottom layer. For example, a random accessible GOSbelongs to the lowermost layer. A GOS that belongs to the same layer ora lower layer is referred to in a GOS that belongs to an upper layer.Stated differently, a GOS is spatially divided in a predetermineddirection in advance to have a plurality of layers, each including atleast one SPC. The encoding device and the decoding device encode ordecode each SPC by referring to a SPC included in the same layer as theeach SPC or a SPC included in a layer lower than that of the each SPC.

Also, the encoding device and the decoding device successively encode ordecode GOSs on a world-by-world basis that includes such GOSs. In sodoing, the encoding device and the decoding device write or read outinformation indicating the order (direction) of encoding or decoding asmetadata. Stated differently, the encoded data includes informationindicating the order of encoding a plurality of GOSs.

The encoding device and the decoding device also encode or decodemutually different two or more SPCs or GOSs in parallel.

Furthermore, the encoding device and the decoding device encode ordecode the spatial information (coordinates, size, etc.) on a SPC or aGOS.

The encoding device and the decoding device encode or decode SPCs orGOSs included in an identified space that is identified on the basis ofexternal information on the self-location or/and region size, such asGPS information, route information, or magnification.

The encoding device or the decoding device gives a lower priority to aspace distant from the self-location than the priority of a nearby spaceto perform encoding or decoding.

The encoding device sets a direction at one of the directions in aworld, in accordance with the magnification or the intended use, toencode a GOS having a layer structure in such direction. Also, thedecoding device decodes a GOS having a layer structure in one of thedirections in a world that has been set in accordance with themagnification or the intended use, preferentially from the bottom layer.

The encoding device changes the accuracy of extracting keypoints, theaccuracy of recognizing objects, or the size of spatial regions, etc.included in a SPC, depending on whether an object is an interior objector an exterior object. Note that the encoding device and the decodingdevice encode or decode an interior GOS and an exterior GOS having closecoordinates in a manner that these GOSs come adjacent to each other in aworld, and associates their identifiers with each other for encoding anddecoding.

Embodiment 2

When using encoded data of a point cloud in an actual device or service,it is desirable that necessary information be transmitted/received inaccordance with the intended use to reduce the network bandwidth.However, there has been no such functionality in the structure ofencoding three-dimensional data, nor an encoding method therefor.

The present embodiment describes a three-dimensional data encodingmethod and a three-dimensional data encoding device for providing thefunctionality of transmitting/receiving only necessary information inencoded data of a three-dimensional point cloud in accordance with theintended use, as well as a three-dimensional data decoding method and athree-dimensional data decoding device for decoding such encoded data.

A voxel (VXL) with a feature greater than or equal to a given amount isdefined as a feature voxel (FVXL), and a world (WLD) constituted byFVXLs is defined as a sparse world (SWLD). FIG. 11 is a diagram showingexample structures of a sparse world and a world. A SWLD includes:FGOSs, each being a GOS constituted by FVXLs; FSPCs, each being a SPCconstituted by FVXLs; and FVLMs, each being a VLM constituted by FVXLs.The data structure and prediction structure of a FGOS, a FSPC, and aFVLM may be the same as those of a GOS, a SPC, and a VLM.

A feature represents the three-dimensional position information on a VXLor the visible-light information on the position of a VXL. A largenumber of features are detected especially at a corner, an edge, etc. ofa three-dimensional object. More specifically, such a feature is athree-dimensional feature or a visible-light feature as described below,but may be any feature that represents the position, luminance, or colorinformation, etc. on a VXL.

Used as three-dimensional features are signature of histograms oforientations (SHOT) features, point feature histograms (PFH) features,or point pair feature (PPF) features.

SHOT features are obtained by dividing the periphery of a VXL, andcalculating an inner product of the reference point and the normalvector of each divided region to represent the calculation result as ahistogram. SHOT features are characterized by a large number ofdimensions and high-level feature representation.

PFH features are obtained by selecting a large number of two point pairsin the vicinity of a VXL, and calculating the normal vector, etc. fromeach two point pair to represent the calculation result as a histogram.PFH features are histogram features, and thus are characterized byrobustness against a certain extent of disturbance and also high-levelfeature representation.

PPF features are obtained by using a normal vector, etc. for each twopoints of VXLs. PPF features, for which all VXLs are used, hasrobustness against occlusion.

Used as visible-light features are scale-invariant feature transform(SIFT), speeded up robust features (SURF), or histogram of orientedgradients (HOG), etc. that use information on an image such as luminancegradient information.

A SWLD is generated by calculating the above-described features of therespective VXLs in a WLD to extract FVXLs. Here, the SWLD may be updatedevery time the WLD is updated, or may be regularly updated after theelapse of a certain period of time, regardless of the timing at whichthe WLD is updated.

A SWLD may be generated for each type of features. For example,different SWLDs may be generated for the respective types of features,such as SWLD1 based on SHOT features and SWLD2 based on SIFT features sothat SWLDs are selectively used in accordance with the intended use.Also, the calculated feature of each FVXL may be held in each FVXL asfeature information.

Next, the usage of a sparse world (SWLD) will be described. A SWLDincludes only feature voxels (FVXLs), and thus its data size is smallerin general than that of a WLD that includes all VXLs.

In an application that utilizes features for a certain purpose, the useof information on a SWLD instead of a WLD reduces the time required toread data from a hard disk, as well as the bandwidth and the timerequired for data transfer over a network. For example, a WLD and a SWLDare held in a server as map information so that map information to besent is selected between the WLD and the SWLD in accordance with arequest from a client. This reduces the network bandwidth and the timerequired for data transfer. More specific examples will be describedbelow.

FIG. 12 and FIG. 13 are diagrams showing usage examples of a SWLD and aWLD. As FIG. 12 shows, when client 1, which is a vehicle-mounted device,requires map information to use it for self-location determination,client 1 sends to a server a request for obtaining map data forself-location estimation (S301). The server sends to client 1 the SWLDin response to the obtainment request (S302). Client 1 uses the receivedSWLD to determine the self-location (S303). In so doing, client 1obtains VXL information on the periphery of client 1 through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.Client 1 then estimates the self-location information from the obtainedVXL information and the SWLD. Here, the self-location informationincludes three-dimensional position information, orientation, etc. ofclient 1.

As FIG. 13 shows, when client 2, which is a vehicle-mounted device,requires map information to use it for rendering a map such as athree-dimensional map, client 2 sends to the server a request forobtaining map data for map rendering (S311). The server sends to client2 the WLD in response to the obtainment request (S312). Client 2 usesthe received WLD to render a map (S313). In so doing, client 2 uses, forexample, an image client 2 has captured by a visible-light camera, etc.and the WLD obtained from the server to create a rendering image, andrenders such created image onto a screen of a car navigation system,etc.

As described above, the server sends to a client a SWLD when thefeatures of the respective VXLs are mainly required such as in the caseof self-location estimation, and sends to a client a WLD when detailedVXL information is required such as in the case of map rendering. Thisallows for an efficient sending/receiving of map data.

Note that a client may self-judge which one of a SWLD and a WLD isnecessary, and request the server to send a SWLD or a WLD. Also, theserver may judge which one of a SWLD and a WLD to send in accordancewith the status of the client or a network.

Next, a method will be described of switching the sending/receivingbetween a sparse world (SWLD) and a world (WLD).

Whether to receive a WLD or a SWLD may be switched in accordance withthe network bandwidth. FIG. 14 is a diagram showing an example operationin such case. For example, when a low-speed network is used that limitsthe usable network bandwidth, such as in a Long-Term Evolution (LTE)environment, a client accesses the server over a low-speed network(S321), and obtains the SWLD from the server as map information (S322).Meanwhile, when a high-speed network is used that has an adequatelybroad network bandwidth, such as in a WiFi environment, a clientaccesses the server over a high-speed network (S323), and obtains theWLD from the server (S324). This enables the client to obtainappropriate map information in accordance with the network bandwidthsuch client is using.

More specifically, a client receives the SWLD over an LTE network whenin outdoors, and obtains the WLD over a WiFi network when in indoorssuch as in a facility. This enables the client to obtain more detailedmap information on indoor environment.

As described above, a client may request for a WLD or a SWLD inaccordance with the bandwidth of a network such client is using.Alternatively, the client may send to the server information indicatingthe bandwidth of a network such client is using, and the server may sendto the client data (the WLD or the SWLD) suitable for such client inaccordance with the information. Alternatively, the server may identifythe network bandwidth the client is using, and send to the client data(the WLD or the SWLD) suitable for such client.

Also, whether to receive a WLD or a SWLD may be switched in accordancewith the speed of traveling. FIG. 15 is a diagram showing an exampleoperation in such case. For example, when traveling at a high speed(S331), a client receives the SWLD from the server (S332). Meanwhile,when traveling at a low speed (S333), the client receives the WLD fromthe server (S334). This enables the client to obtain map informationsuitable to the speed, while reducing the network bandwidth. Morespecifically, when traveling on an expressway, the client receives theSWLD with a small data amount, which enables the update of rough mapinformation at an appropriate speed. Meanwhile, when traveling on ageneral road, the client receives the WLD, which enables the obtainmentof more detailed map information.

As described above, the client may request the server for a WLD or aSWLD in accordance with the traveling speed of such client.Alternatively, the client may send to the server information indicatingthe traveling speed of such client, and the server may send to theclient data (the WLD or the SWLD) suitable to such client in accordancewith the information. Alternatively, the server may identify thetraveling speed of the client to send data (the WLD or the SWLD)suitable to such client.

Also, the client may obtain, from the server, a SWLD first, from whichthe client may obtain a WLD of an important region. For example, whenobtaining map information, the client first obtains a SWLD for rough mapinformation, from which the client narrows to a region in which featuressuch as buildings, signals, or persons appear at high frequency so thatthe client can later obtain a WLD of such narrowed region. This enablesthe client to obtain detailed information on a necessary region, whilereducing the amount of data received from the server.

The server may also create from a WLD different SWLDs for the respectiveobjects, and the client may receive SWLDs in accordance with theintended use. This reduces the network bandwidth. For example, theserver recognizes persons or cars in a WLD in advance, and creates aSWLD of persons and a SWLD of cars. The client, when wishing to obtaininformation on persons around the client, receives the SWLD of persons,and when wising to obtain information on cars, receives the SWLD ofcars. Such types of SWLDs may be distinguished by information (flag, ortype, etc.) added to the header, etc.

Next, the structure and the operation flow of the three-dimensional dataencoding device (e.g., a server) according to the present embodimentwill be described. FIG. 16 is a block diagram of three-dimensional dataencoding device 400 according to the present embodiment. FIG. 17 is aflowchart of three-dimensional data encoding processes performed bythree-dimensional data encoding device 400.

Three-dimensional data encoding device 400 shown in FIG. 16 encodesinput three-dimensional data 411, thereby generating encodedthree-dimensional data 413 and encoded three-dimensional data 414, eachbeing an encoded stream. Here, encoded three-dimensional data 413 isencoded three-dimensional data corresponding to a WLD, and encodedthree-dimensional data 414 is encoded three-dimensional datacorresponding to a SWLD. Such three-dimensional data encoding device 400includes, obtainer 401, encoding region determiner 402, SWLD extractor403, WLD encoder 404, and SWLD encoder 405.

First, as FIG. 17 shows, obtainer 401 obtains input three-dimensionaldata 411, which is point group data in a three-dimensional space (S401).

Next, encoding region determiner 402 determines a current spatial regionfor encoding on the basis of a spatial region in which the point clouddata is present (S402).

Next, SWLD extractor 403 defines the current spatial region as a WLD,and calculates the feature from each VXL included in the WLD. Then, SWLDextractor 403 extracts VXLs having an amount of features greater than orequal to a predetermined threshold, defines the extracted VXLs as FVXLs,and adds such FVXLs to a SWLD, thereby generating extractedthree-dimensional data 412 (S403). Stated differently, extractedthree-dimensional data 412 having an amount of features greater than orequal to the threshold is extracted from input three-dimensional data411.

Next, WLD encoder 404 encodes input three-dimensional data 411corresponding to the WLD, thereby generating encoded three-dimensionaldata 413 corresponding to the WLD (S404). In so doing, WLD encoder 404adds to the header of encoded three-dimensional data 413 informationthat distinguishes that such encoded three-dimensional data 413 is astream including a WLD.

SWLD encoder 405 encodes extracted three-dimensional data 412corresponding to the SWLD, thereby generating encoded three-dimensionaldata 414 corresponding to the SWLD (S405). In so doing, SWLD encoder 405adds to the header of encoded three-dimensional data 414 informationthat distinguishes that such encoded three-dimensional data 414 is astream including a SWLD.

Note that the process of generating encoded three-dimensional data 413and the process of generating encoded three-dimensional data 414 may beperformed in the reverse order. Also note that a part or all of theseprocesses may be performed in parallel.

A parameter “world_type” is defined, for example, as information addedto each header of encoded three-dimensional data 413 and encodedthree-dimensional data 414. world_type=0 indicates that a streamincludes a WLD, and world_type=1 indicates that a stream includes aSWLD. An increased number of values may be further assigned to define alarger number of types, e.g., world_type=2. Also, one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 mayinclude a specified flag. For example, encoded three-dimensional data414 may be assigned with a flag indicating that such stream includes aSWLD. In such a case, the decoding device can distinguish whether suchstream is a stream including a WLD or a stream including a SWLD inaccordance with the presence/absence of the flag.

Also, an encoding method used by WLD encoder 404 to encode a WLD may bedifferent from an encoding method used by SWLD encoder 405 to encode aSWLD.

For example, data of a SWLD is decimated, and thus can have a lowercorrelation with the neighboring data than that of a WLD. For thisreason, of intra prediction and inter prediction, inter prediction maybe more preferentially performed in an encoding method used for a SWLDthan in an encoding method used for a WLD.

Also, an encoding method used for a SWLD and an encoding method used fora WLD may represent three-dimensional positions differently. Forexample, three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Also, SWLD encoder 405 performs encoding in a manner that encodedthree-dimensional data 414 of a SWLD has a smaller data size than thedata size of encoded three-dimensional data 413 of a WLD. A SWLD canhave a lower inter-data correlation, for example, than that of a WLD asdescribed above. This can lead to a decreased encoding efficiency, andthus to encoded three-dimensional data 414 having a larger data sizethan the data size of encoded three-dimensional data 413 of a WLD. Whenthe data size of the resulting encoded three-dimensional data 414 islarger than the data size of encoded three-dimensional data 413 of aWLD, SWLD encoder 405 performs encoding again to re-generate encodedthree-dimensional data 414 having a reduced data size.

For example, SWLD extractor 403 re-generates extracted three-dimensionaldata 412 having a reduced number of keypoints to be extracted, and SWLDencoder 405 encodes such extracted three-dimensional data 412.Alternatively, SWLD encoder 405 may perform more coarse quantization.More coarse quantization is achieved, for example, by rounding the datain the lowermost level in an octree structure described below.

When failing to decrease the data size of encoded three-dimensional data414 of the SWLD to smaller than the data size of encodedthree-dimensional data 413 of the WLD, SWLD encoder 405 may not generateencoded three-dimensional data 414 of the SWLD. Alternatively, encodedthree-dimensional data 413 of the WLD may be copied as encodedthree-dimensional data 414 of the SWLD. Stated differently, encodedthree-dimensional data 413 of the WLD may be used as it is as encodedthree-dimensional data 414 of the SWLD.

Next, the structure and the operation flow of the three-dimensional datadecoding device (e.g., a client) according to the present embodimentwill be described. FIG. 18 is a block diagram of three-dimensional datadecoding device 500 according to the present embodiment. FIG. 19 is aflowchart of three-dimensional data decoding processes performed bythree-dimensional data decoding device 500.

Three-dimensional data decoding device 500 shown in FIG. 18 decodesencoded three-dimensional data 511, thereby generating decodedthree-dimensional data 512 or decoded three-dimensional data 513.Encoded three-dimensional data 511 here is, for example, encodedthree-dimensional data 413 or encoded three-dimensional data 414generated by three-dimensional data encoding device 400.

Such three-dimensional data decoding device 500 includes obtainer 501,header analyzer 502, WLD decoder 503, and SWLD decoder 504.

First, as FIG. 19 shows, obtainer 501 obtains encoded three-dimensionaldata 511 (S501). Next, header analyzer 502 analyzes the header ofencoded three-dimensional data 511 to identify whether encodedthree-dimensional data 511 is a stream including a WLD or a streamincluding a SWLD (S502). For example, the above-described parameterworld_type is referred to in making such identification.

When encoded three-dimensional data 511 is a stream including a WLD (Yesin S503), WLD decoder 503 decodes encoded three-dimensional data 511,thereby generating decoded three-dimensional data 512 of the WLD (S504).Meanwhile, when encoded three-dimensional data 511 is a stream includinga SWLD (No in S503), SWLD decoder 504 decodes encoded three-dimensionaldata 511, thereby generating decoded three-dimensional data 513 of theSWLD (S505).

Also, as in the case of the encoding device, a decoding method used byWLD decoder 503 to decode a WLD may be different from a decoding methodused by SWLD decoder 504 to decode a SWLD. For example, of intraprediction and inter prediction, inter prediction may be morepreferentially performed in a decoding method used for a SWLD than in adecoding method used for a WLD.

Also, a decoding method used for a SWLD and a decoding method used for aWLD may represent three-dimensional positions differently. For example,three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Next, an octree representation will be described, which is a method ofrepresenting three-dimensional positions. VXL data included inthree-dimensional data is converted into an octree structure beforeencoded. FIG. 20 is a diagram showing example VXLs in a WLD. FIG. 21 isa diagram showing an octree structure of the WLD shown in FIG. 20. Anexample shown in FIG. 20 illustrates three VXLs 1 to 3 that includepoint groups (hereinafter referred to as effective VXLs). As FIG. 21shows, the octree structure is made of nodes and leaves. Each node has amaximum of eight nodes or leaves. Each leaf has VXL information. Here,of the leaves shown in FIG. 21, leaf 1, leaf 2, and leaf 3 representVXL1, VXL2, and VXL3 shown in FIG. 20, respectively.

More specifically, each node and each leaf correspond to athree-dimensional position. Node 1 corresponds to the entire block shownin FIG. 20. The block that corresponds to node 1 is divided into eightblocks. Of these eight blocks, blocks including effective VXLs are setas nodes, while the other blocks are set as leaves. Each block thatcorresponds to a node is further divided into eight nodes or leaves.These processes are repeated by the number of times that is equal to thenumber of levels in the octree structure. All blocks in the lowermostlevel are set as leaves.

FIG. 22 is a diagram showing an example SWLD generated from the WLDshown in FIG. 20. VXL1 and VXL2 shown in FIG. 20 are judged as FVXL1 andFVXL2 as a result of feature extraction, and thus are added to the SWLD.Meanwhile, VXL3 is not judged as a FVXL, and thus is not added to theSWLD. FIG. 23 is a diagram showing an octree structure of the SWLD shownin FIG. 22. In the octree structure shown in FIG. 23, leaf 3corresponding to VXL3 shown in FIG. 21 is deleted. Consequently, node 3shown in FIG. 21 has lost an effective VXL, and has changed to a leaf.As described above, a SWLD has a smaller number of leaves in generalthan a WLD does, and thus the encoded three-dimensional data of the SWLDis smaller than the encoded three-dimensional data of the WLD.

The following describes variations of the present embodiment.

For self-location estimation, for example, a client, being avehicle-mounted device, etc., may receive a SWLD from the server to usesuch SWLD to estimate the self-location. Meanwhile, for obstacledetection, the client may detect obstacles by use of three-dimensionalinformation on the periphery obtained by such client through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.

In general, a SWLD is less likely to include VXL data on a flat region.As such, the server may hold a subsample world (subWLD) obtained bysubsampling a WLD for detection of static obstacles, and send to theclient the SWLD and the subWLD. This enables the client to performself-location estimation and obstacle detection on the client's part,while reducing the network bandwidth.

When the client renders three-dimensional map data at a high speed, mapinformation having a mesh structure is more useful in some cases. Assuch, the server may generate a mesh from a WLD to hold it beforehand asa mesh world (MWLD). For example, when wishing to perform coarsethree-dimensional rendering, the client receives a MWLD, and whenwishing to perform detailed three-dimensional rendering, the clientreceives a WLD. This reduces the network bandwidth.

In the above description, the server sets, as FVXLs, VXLs having anamount of features greater than or equal to the threshold, but theserver may calculate FVXLs by a different method. For example, theserver may judge that a VXL, a VLM, a SPC, or a GOS that constitutes asignal, or an intersection, etc. as necessary for self-locationestimation, driving assist, or self-driving, etc., and incorporate suchVXL, VLM, SPC, or GOS into a SWLD as a FVXL, a FVLM, a FSPC, or a FGOS.Such judgment may be made manually. Also, FVXLs, etc. that have been seton the basis of an amount of features may be added to FVXLs, etc.obtained by the above method. Stated differently, SWLD extractor 403 mayfurther extract, from input three-dimensional data 411, datacorresponding to an object having a predetermined attribute as extractedthree-dimensional data 412. Also, that a VXL, a VLM, a SPC, or a GOS isnecessary for such intended usage may be labeled separately from thefeatures. The server may separately hold, as an upper layer of a SWLD(e.g., a lane world), FVXLs of a signal or an intersection, etc.necessary for self-location estimation, driving assist, or self-driving,etc.

The server may also add an attribute to VXLs in a WLD on a random accessbasis or on a predetermined unit basis. An attribute, for example,includes information indicating whether VXLs are necessary forself-location estimation, or information indicating whether VXLs areimportant as traffic information such as a signal, or an intersection,etc. An attribute may also include a correspondence between VXLs andfeatures (intersection, or road, etc.) in lane information (geographicdata files (GDF), etc.).

A method as described below may be used to update a WLD or a SWLD.

Update information indicating changes, etc. in a person, a roadwork, ora tree line (for trucks) is uploaded to the server as point groups ormeta data. The server updates a WLD on the basis of such uploadedinformation, and then updates a SWLD by use of the updated WLD.

The client, when detecting a mismatch between the three-dimensionalinformation such client has generated at the time of self-locationestimation and the three-dimensional information received from theserver, may send to the server the three-dimensional information suchclient has generated, together with an update notification. In such acase, the server updates the SWLD by use of the WLD. When the SWLD isnot to be updated, the server judges that the WLD itself is old.

In the above description, information that distinguishes whether anencoded stream is that of a WLD or a SWLD is added as header informationof the encoded stream. However, when there are many types of worlds suchas a mesh world and a lane world, information that distinguishes thesetypes of the worlds may be added to header information. Also, when thereare many SWLDs with different amounts of features, information thatdistinguishes the respective SWLDs may be added to header information.

In the above description, a SWLD is constituted by FVXLs, but a SWLD mayinclude VXLs that have not been judged as FVXLs. For example, a SWLD mayinclude an adjacent VXL used to calculate the feature of a FVXL. Thisenables the client to calculate the feature of a FVXL when receiving aSWLD, even in the case where feature information is not added to eachFVXL of the SWLD. In such a case, the SWLD may include information thatdistinguishes whether each VXL is a FVXL or a VXL.

As described above, three-dimensional data encoding device 400 extracts,from input three-dimensional data 411 (first three-dimensional data),extracted three-dimensional data 412 (second three-dimensional data)having an amount of a feature greater than or equal to a threshold, andencodes extracted three-dimensional data 412 to generate encodedthree-dimensional data 414 (first encoded three-dimensional data).

This three-dimensional data encoding device 400 generates encodedthree-dimensional data 414 that is obtained by encoding data having anamount of a feature greater than or equal to the threshold. This reducesthe amount of data compared to the case where input three-dimensionaldata 411 is encoded as it is. Three-dimensional data encoding device 400is thus capable of reducing the amount of data to be transmitted.

Three-dimensional data encoding device 400 further encodes inputthree-dimensional data 411 to generate encoded three-dimensional data413 (second encoded three-dimensional data).

This three-dimensional data encoding device 400 enables selectivetransmission of encoded three-dimensional data 413 and encodedthree-dimensional data 414, in accordance, for example, with theintended use, etc.

Also, extracted three-dimensional data 412 is encoded by a firstencoding method, and input three-dimensional data 411 is encoded by asecond encoding method different from the first encoding method.

This three-dimensional data encoding device 400 enables the use of anencoding method suitable for each of input three-dimensional data 411and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first encoding method than in thesecond encoding method.

This three-dimensional data encoding device 400 enables inter predictionto be more preferentially performed on extracted three-dimensional data412 in which adjacent data items are likely to have low correlation.

Also, the first encoding method and the second encoding method representthree-dimensional positions differently. For example, the secondencoding method represents three-dimensional positions by octree, andthe first encoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data encoding device 400 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411. Stated differently, such identifierindicates whether the encoded three-dimensional data is encodedthree-dimensional data 413 of a WLD or encoded three-dimensional data414 of a SWLD.

This enables the decoding device to readily judge whether the obtainedencoded three-dimensional data is encoded three-dimensional data 413 orencoded three-dimensional data 414.

Also, three-dimensional data encoding device 400 encodes extractedthree-dimensional data 412 in a manner that encoded three-dimensionaldata 414 has a smaller data amount than a data amount of encodedthree-dimensional data 413.

This three-dimensional data encoding device 400 enables encodedthree-dimensional data 414 to have a smaller data amount than the dataamount of encoded three-dimensional data 413.

Also, three-dimensional data encoding device 400 further extracts datacorresponding to an object having a predetermined attribute from inputthree-dimensional data 411 as extracted three-dimensional data 412. Theobject having a predetermined attribute is, for example, an objectnecessary for self-location estimation, driving assist, or self-driving,etc., or more specifically, a signal, an intersection, etc.

This three-dimensional data encoding device 400 is capable of generatingencoded three-dimensional data 414 that includes data required by thedecoding device.

Also, three-dimensional data encoding device 400 (server) further sends,to a client, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a status of the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Also, three-dimensional data encoding device 400 further sends, to aclient, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a request from the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the request from the client.

Also, three-dimensional data decoding device 500 according to thepresent embodiment decodes encoded three-dimensional data 413 or encodedthree-dimensional data 414 generated by three-dimensional data encodingdevice 400 described above.

Stated differently, three-dimensional data decoding device 500 decodes,by a first decoding method, encoded three-dimensional data 414 obtainedby encoding extracted three-dimensional data 412 having an amount of afeature greater than or equal to a threshold, extractedthree-dimensional data 412 having been extracted from inputthree-dimensional data 411. Three-dimensional data decoding device 500also decodes, by a second decoding method, encoded three-dimensionaldata 413 obtained by encoding input three-dimensional data 411, thesecond decoding method being different from the first decoding method.

This three-dimensional data decoding device 500 enables selectivereception of encoded three-dimensional data 414 obtained by encodingdata having an amount of a feature greater than or equal to thethreshold and encoded three-dimensional data 413, in accordance, forexample, with the intended use, etc. Three-dimensional data decodingdevice 500 is thus capable of reducing the amount of data to betransmitted. Such three-dimensional data decoding device 500 furtherenables the use of a decoding method suitable for each of inputthree-dimensional data 411 and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first decoding method than in thesecond decoding method.

This three-dimensional data decoding device 500 enables inter predictionto be more preferentially performed on the extracted three-dimensionaldata in which adjacent data items are likely to have low correlation.

Also, the first decoding method and the second decoding method representthree-dimensional positions differently. For example, the seconddecoding method represents three-dimensional positions by octree, andthe first decoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data decoding device 500 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411. Three-dimensional data decoding device 500refers to such identifier in identifying between encodedthree-dimensional data 413 and encoded three-dimensional data 414.

This three-dimensional data decoding device 500 is capable of readilyjudging whether the obtained encoded three-dimensional data is encodedthree-dimensional data 413 or encoded three-dimensional data 414.

Three-dimensional data decoding device 500 further notifies a server ofa status of the client (three-dimensional data decoding device 500).

Three-dimensional data decoding device 500 receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the status of the client.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Three-dimensional data decoding device 500 further makes a request ofthe server for one of encoded three-dimensional data 413 and encodedthree-dimensional data 414, and receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the request.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the intended use.

Embodiment 3

The present embodiment will describe a method of transmitting/receivingthree-dimensional data between vehicles.

FIG. 24 is a schematic diagram showing three-dimensional data 607 beingtransmitted/received between own vehicle 600 and nearby vehicle 601.

In three-dimensional data that is obtained by a sensor mounted on ownvehicle 600 (e.g., a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras),there appears a region, three-dimensional data of which cannot becreated, due to an obstacle such as nearby vehicle 601, despite thatsuch region is included in sensor detection range 602 of own vehicle 600(such region is hereinafter referred to as occlusion region 604). Also,while the obtainment of three-dimensional data of a larger space enablesa higher accuracy of autonomous operations, a range of sensor detectiononly by own vehicle 600 is limited.

Sensor detection range 602 of own vehicle 600 includes region 603,three-dimensional data of which is obtainable, and occlusion region 604.A range, three-dimensional data of which own vehicle 600 wishes toobtain, includes sensor detection range 602 of own vehicle 600 and otherregions. Sensor detection range 605 of nearby vehicle 601 includesocclusion region 604 and region 606 that is not included in sensordetection range 602 of own vehicle 600.

Nearby vehicle 601 transmits information detected by nearby vehicle 601to own vehicle 600. Own vehicle 600 obtains the information detected bynearby vehicle 601, such as a preceding vehicle, thereby obtainingthree-dimensional data 607 of occlusion region 604 and region 606outside of sensor detection range 602 of own vehicle 600. Own vehicle600 uses the information obtained by nearby vehicle 601 to complementthe three-dimensional data of occlusion region 604 and region 606outside of the sensor detection range.

The usage of three-dimensional data in autonomous operations of avehicle or a robot includes self-location estimation, detection ofsurrounding conditions, or both. For example, for self-locationestimation, three-dimensional data is used that is generated by ownvehicle 600 on the basis of sensor information of own vehicle 600. Fordetection of surrounding conditions, three-dimensional data obtainedfrom nearby vehicle 601 is also used in addition to thethree-dimensional data generated by own vehicle 600.

Nearby vehicle 601 that transmits three-dimensional data 607 to ownvehicle 600 may be determined in accordance with the state of ownvehicle 600. For example, the current nearby vehicle 601 is a precedingvehicle when own vehicle 600 is running straight ahead, an oncomingvehicle when own vehicle 600 is turning right, and a following vehiclewhen own vehicle 600 is rolling backward. Alternatively, the driver ofown vehicle 600 may directly specify nearby vehicle 601 that transmitsthree-dimensional data 607 to own vehicle 600.

Alternatively, own vehicle 600 may search for nearby vehicle 601 havingthree-dimensional data of a region that is included in a space,three-dimensional data of which own vehicle 600 wishes to obtain, andthat own vehicle 600 cannot obtain. The region own vehicle 600 cannotobtain is occlusion region 604, or region 606 outside of sensordetection range 602, etc.

Own vehicle 600 may identify occlusion region 604 on the basis of thesensor information of own vehicle 600. For example, own vehicle 600identifies, as occlusion region 604, a region which is included insensor detection range 602 of own vehicle 600, and three-dimensionaldata of which cannot be created.

The following describes example operations to be performed when avehicle that transmits three-dimensional data 607 is a precedingvehicle. FIG. 25 is a diagram showing an example of three-dimensionaldata to be transmitted in such case.

As FIG. 25 shows, three-dimensional data 607 transmitted from thepreceding vehicle is, for example, a sparse world (SWLD) of a pointcloud. Stated differently, the preceding vehicle createsthree-dimensional data (point cloud) of a WLD from information detectedby a sensor of such preceding vehicle, and extracts data having anamount of features greater than or equal to the threshold from suchthree-dimensional data of the WLD, thereby creating three-dimensionaldata (point cloud) of the SWLD. Subsequently, the preceding vehicletransmits the created three-dimensional data of the SWLD to own vehicle600.

Own vehicle 600 receives the SWLD, and merges the received SWLD with thepoint cloud created by own vehicle 600.

The SWLD to be transmitted includes information on the absolutecoordinates (the position of the SWLD in the coordinates system of athree-dimensional map). The merge is achieved by own vehicle 600overwriting the point cloud generated by own vehicle 600 on the basis ofsuch absolute coordinates.

The SWLD transmitted from nearby vehicle 601 may be: a SWLD of region606 that is outside of sensor detection range 602 of own vehicle 600 andwithin sensor detection range 605 of nearby vehicle 601; or a SWLD ofocclusion region 604 of own vehicle 600; or the SWLDs of the both. Ofthese SWLDs, a SWLD to be transmitted may also be a SWLD of a regionused by nearby vehicle 601 to detect the surrounding conditions.

Nearby vehicle 601 may change the density of a point cloud to transmit,in accordance with the communication available time, during which ownvehicle 600 and nearby vehicle 601 can communicate, and which is basedon the speed difference between these vehicles. For example, when thespeed difference is large and the communication available time is short,nearby vehicle 601 may extract three-dimensional points having a largeamount of features from the SWLD to decrease the density (data amount)of the point cloud.

The detection of the surrounding conditions refers to judging thepresence/absence of persons, vehicles, equipment for roadworks, etc.,identifying their types, and detecting their positions, travellingdirections, traveling speeds, etc.

Own vehicle 600 may obtain braking information of nearby vehicle 601instead of or in addition to three-dimensional data 607 generated bynearby vehicle 601. Here, the braking information of nearby vehicle 601is, for example, information indicating that the accelerator or thebrake of nearby vehicle 601 has been pressed, or the degree of suchpressing.

In the point clouds generated by the vehicles, the three-dimensionalspaces are segmented on a random access unit, in consideration oflow-latency communication between the vehicles. Meanwhile, in athree-dimensional map, etc., which is map data downloaded from theserver, a three-dimensional space is segmented in a larger random accessunit than in the case of inter-vehicle communication.

Data on a region that is likely to be an occlusion region, such as aregion in front of the preceding vehicle and a region behind thefollowing vehicle, is segmented on a finer random access unit aslow-latency data.

Data on a region in front of a vehicle has an increased importance whenon an expressway, and thus each vehicle creates a SWLD of a range with anarrowed viewing angle on a finer random access unit when running on anexpressway.

When the SWLD created by the preceding vehicle for transmission includesa region, the point cloud of which own vehicle 600 can obtain, thepreceding vehicle may remove the point cloud of such region to reducethe amount of data to transmit.

Next, the structure and operations of three-dimensional data creationdevice 620 will be described, which is the three-dimensional datareception device according to the present embodiment.

FIG. 26 is a block diagram of three-dimensional data creation device 620according to the present embodiment. Such three-dimensional datacreation device 620, which is included, for example, in theabove-described own vehicle 600, mergers first three-dimensional data632 created by three-dimensional data creation device 620 with thereceived second three-dimensional data 635, thereby creating thirdthree-dimensional data 636 having a higher density.

Such three-dimensional data creation device 620 includesthree-dimensional data creator 621, request range determiner 622,searcher 623, receiver 624, decoder 625, and merger 626. FIG. 27 is aflowchart of operations performed by three-dimensional data creationdevice 620.

First, three-dimensional data creator 621 creates firstthree-dimensional data 632 by use of sensor information 631 detected bythe sensor included in own vehicle 600 (S621). Next, request rangedeterminer 622 determines a request range, which is the range of athree-dimensional space, the data on which is insufficient in thecreated first three-dimensional data 632 (S622).

Next, searcher 623 searches for nearby vehicle 601 having thethree-dimensional data of the request range, and sends request rangeinformation 633 indicating the request range to nearby vehicle 601having been searched out (S623). Next, receiver 624 receives encodedthree-dimensional data 634, which is an encoded stream of the requestrange, from nearby vehicle 601 (S624). Note that searcher 623 mayindiscriminately send requests to all vehicles included in a specifiedrange to receive encoded three-dimensional data 634 from a vehicle thathas responded to the request. Searcher 623 may send a request not onlyto vehicles but also to an object such as a signal and a sign, andreceive encoded three-dimensional data 634 from the object.

Next, decoder 625 decodes the received encoded three-dimensional data634, thereby obtaining second three-dimensional data 635 (S625). Next,merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635, thereby creating three-dimensional data 636having a higher density (S626). Next, the structure and operations ofthree-dimensional data transmission device 640 according to the presentembodiment will be described. FIG. 28 is a block diagram ofthree-dimensional data transmission device 640.

Three-dimensional data transmission device 640 is included, for example,in the above-described nearby vehicle 601. Three-dimensional datatransmission device 640 processes fifth three-dimensional data 652created by nearby vehicle 601 into sixth three-dimensional data 654requested by own vehicle 600, encodes sixth three-dimensional data 654to generate encoded three-dimensional data 634, and sends encodedthree-dimensional data 634 to own vehicle 600.

Three-dimensional data transmission device 640 includesthree-dimensional data creator 641, receiver 642, extractor 643, encoder644, and transmitter 645. FIG. 29 is a flowchart of operations performedby three-dimensional data transmission device 640.

First, three-dimensional data creator 641 creates fifththree-dimensional data 652 by use of sensor information 651 detected bythe sensor included in nearby vehicle 601 (S641). Next, receiver 642receives request range information 633 from own vehicle 600 (S642).

Next, extractor 643 extracts from fifth three-dimensional data 652 thethree-dimensional data of the request range indicated by request rangeinformation 633, thereby processing fifth three-dimensional data 652into sixth three-dimensional data 654 (S643). Next, encoder 644 encodessixth three-dimensional data 654 to generate encoded three-dimensionaldata 643, which is an encoded stream (S644). Then, transmitter 645 sendsencoded three-dimensional data 634 to own vehicle 600 (S645).

Note that although an example case is described here in which ownvehicle 600 includes three-dimensional data creation device 620 andnearby vehicle 601 includes three-dimensional data transmission device640, each of the vehicles may include the functionality of boththree-dimensional data creation device 620 and three-dimensional datatransmission device 640.

The following describes the structure and operations ofthree-dimensional data creation device 620 when three-dimensional datacreation device 620 is a surrounding condition detection device thatenables the detection of the surrounding conditions of own vehicle 600.FIG. 30 is a block diagram of the structure of three-dimensional datacreation device 620A in such case. Three-dimensional data creationdevice 620A shown in FIG. 30 further includes detection regiondeterminer 627, surrounding condition detector 628, and autonomousoperation controller 629, in addition to the components ofthree-dimensional data creation device 620 shown in FIG. 26.Three-dimensional data creation device 620A is included in own vehicle600.

FIG. 31 is a flowchart of processes, performed by three-dimensional datacreation device 620A, of detecting the surrounding conditions of ownvehicle 600.

First, three-dimensional data creator 621 creates firstthree-dimensional data 632, which is a point cloud, by use of sensorinformation 631 on the detection range of own vehicle 600 detected bythe sensor of own vehicle 600 (S661). Note that three-dimensional datacreation device 620A may further estimate the self-location by use ofsensor information 631.

Next, detection region determiner 627 determines a target detectionrange, which is a spatial region, the surrounding conditions of whichare wished to be detected (S662). For example, detection regiondeterminer 627 calculates a region that is necessary for the detectionof the surrounding conditions, which is an operation required for safeautonomous operations (self-driving), in accordance with the conditionsof autonomous operations, such as the direction and speed of travelingof own vehicle 600, and determines such region as the target detectionrange.

Next, request range determiner 622 determines, as a request range,occlusion region 604 and a spatial region that is outside of thedetection range of the sensor of own vehicle 600 but that is necessaryfor the detection of the surrounding conditions (S663).

When the request range determined in step S663 is present (Yes in S664),searcher 623 searches for a nearby vehicle having information on therequest range. For example, searcher 623 may inquire about whether anearby vehicle has information on the request range, or may judgewhether a nearby vehicle has information on the request range, on thebasis of the positions of the request range and such nearby vehicle.Next, searcher 623 sends, to nearby vehicle 601 having been searchedout, request signal 637 that requests for the transmission ofthree-dimensional data. Searcher 623 then receives an acceptance signalfrom nearby vehicle 601 indicating that the request of request signal637 has been accepted, after which searcher 623 sends request rangeinformation 633 indicating the request range to nearby vehicle 601(S665).

Next, receiver 624 detects a notice that transmission data 638 has beentransmitted, which is the information on the request range, and receivessuch transmission data 638 (S666).

Note that three-dimensional data creation device 620A mayindiscriminately send requests to all vehicles in a specified range andreceive transmission data 638 from a vehicle that has sent a responseindicating that such vehicle has the information on the request range,without searching for a vehicle to send a request to. Searcher 623 maysend a request not only to vehicles but also to an object such as asignal and a sign, and receive transmission data 638 from such object.

Transmission data 638 includes at least one of the following generatedby nearby vehicle 601: encoded three-dimensional data 634, which isencoded three-dimensional data of the request range; and surroundingcondition detection result 639 of the request range. Surroundingcondition detection result 639 indicates the positions, travelingdirections and traveling speeds, etc., of persons and vehicles detectedby nearby vehicle 601. Transmission data 638 may also includeinformation indicating the position, motion, etc., of nearby vehicle601. For example, transmission data 638 may include braking informationof nearby vehicle 601.

When the received transmission data 638 includes encodedthree-dimensional data 634 (Yes in 667), decoder 625 decodes encodedthree-dimensional data 634 to obtain second three-dimensional data 635of the SWLD (S668). Stated differently, second three-dimensional data635 is three-dimensional data (SWLD) that has been generated byextracting data having an amount of features greater than or equal tothe threshold from fourth three-dimensional data (WLD).

Next, merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635, thereby generating third three-dimensionaldata 636 (S669).

Next, surrounding condition detector 628 detects the surroundingconditions of own vehicle 600 by use of third three-dimensional data636, which is a point cloud of a spatial region necessary to detect thesurrounding conditions (S670). Note that when the received transmissiondata 638 includes surrounding condition detection result 639,surrounding condition detector 628 detects the surrounding conditions ofown vehicle 600 by use of surrounding condition detection result 639, inaddition to third three-dimensional data 636. When the receivedtransmission data 638 includes the braking information of nearby vehicle601, surrounding condition detector 628 detects the surroundingconditions of own vehicle 600 by use of such braking information, inaddition to third three-dimensional data 636.

Next, autonomous operation controller 629 controls the autonomousoperations (self-driving) of own vehicle 600 on the basis of thesurrounding condition detection result obtained by surrounding conditiondetector 628 (S671). Note that the surrounding condition detectionresult may be presented to the driver via a user interface (UI), etc.

Meanwhile, when the request range is not present in step S663 (No inS664), or stated differently, when information on all spatial regionsnecessary to detect the surrounding conditions has been created on thebasis of sensor information 631, surrounding condition detector 628detects the surrounding conditions of own vehicle 600 by use of firstthree-dimensional data 632, which is the point cloud of the spatialregion necessary to detect the surrounding conditions (S672). Then,autonomous operation controller 629 controls the autonomous operations(self-driving) of own vehicle 600 on the basis of the surroundingcondition detection result obtained by surrounding condition detector628 (S671).

Meanwhile, when the received transmission data 638 does not includeencoded three-dimensional data 634 (No in S667), or stated differently,when transmission data 638 includes only surrounding condition detectionresult 639 or the braking information of nearby vehicle 601, surroundingcondition detector 628 detects the surrounding conditions of own vehicle600 by use of first three-dimensional data 632, and surroundingcondition detection result 639 or the braking information (S673). Then,autonomous operation controller 629 controls the autonomous operations(self-driving) of own vehicle 600 on the basis of the surroundingcondition detection result obtained by surrounding condition detector628 (S671).

Next, three-dimensional data transmission device 640A will be describedthat transmits transmission data 638 to the above-describedthree-dimensional data creation device 620A. FIG. 32 is a block diagramof such three-dimensional data transmission device 640A.

Three-dimensional data transmission device 640A shown in FIG. 32 furtherincludes transmission permissibility judgment unit 646, in addition tothe components of three-dimensional data transmission device 640 shownin FIG. 28. Three-dimensional data transmission device 640A is includedin nearby vehicle 601.

FIG. 33 is a flowchart of example operations performed bythree-dimensional data transmission device 640A. First,three-dimensional data creator 641 creates fifth three-dimensional data652 by use of sensor information 651 detected by the sensor included innearby vehicle 601 (S681).

Next, receiver 642 receives from own vehicle 600 request signal 637 thatrequests for the transmission of three-dimensional data (S682). Next,transmission permissibility judgment unit 646 determines whether toaccept the request indicated by request signal 637 (S683). For example,transmission permissibility judgment unit 646 determines whether toaccept the request on the basis of the details previously set by theuser. Note that receiver 642 may receive a request from the other endsuch as a request range beforehand, and transmission permissibilityjudgment unit 646 may determine whether to accept the request inaccordance with the details of such request. For example, transmissionpermissibility judgment unit 646 may determine to accept the requestwhen the three-dimensional data transmission device has thethree-dimensional data of the request range, and not to accept therequest when the three-dimensional data transmission device does nothave the three-dimensional data of the request range.

When determining to accept the request (Yes in S683), three-dimensionaldata transmission device 640A sends a permission signal to own vehicle600, and receiver 642 receives request range information 633 indicatingthe request range (S684). Next, extractor 643 extracts the point cloudof the request range from fifth three-dimensional data 652, which is apoint cloud, and creates transmission data 638 that includes sixththree-dimensional data 654, which is the SWLD of the extracted pointcloud (S685).

Stated differently, three-dimensional data transmission device 640Acreates seventh three-dimensional data (WLD) from sensor information651, and extracts data having an amount of features greater than orequal to the threshold from seventh three-dimensional data (WLD),thereby creating fifth three-dimensional data 652 (SWLD). Note thatthree-dimensional data creator 641 may create three-dimensional data ofa SWLD beforehand, from which extractor 643 may extractthree-dimensional data of a SWLD of the request range. Alternatively,extractor 643 may generate three-dimensional data of the SWLD of therequest range from the three-dimensional data of the WLD of the requestrange.

Transmission data 638 may include surrounding condition detection result639 of the request range obtained by nearby vehicle 601 and the brakinginformation of nearby vehicle 601. Transmission data 638 may includeonly at least one of surrounding condition detection result 639 of therequest range obtained by nearby vehicle 601 and the braking informationof nearby vehicle 601, without including sixth three-dimensional data654.

When transmission data 638 includes sixth three-dimensional data 654(Yes in S686), encoder 644 encodes sixth three-dimensional data 654 togenerate encoded three-dimensional data 634 (S687).

Then, transmitter 645 sends to own vehicle 600 transmission data 638that includes encoded three-dimensional data 634 (S688).

Meanwhile, when transmission data 638 does not include sixththree-dimensional data 654 (No in S686), transmitter 645 sends to ownvehicle 600 transmission data 638 that includes at least one ofsurrounding condition detection result 639 of the request range obtainedby nearby vehicle 601 and the braking information of nearby vehicle 601(S688).

The following describes variations of the present embodiment.

For example, information transmitted from nearby vehicle 601 may not bethree-dimensional data or a surrounding condition detection resultgenerated by the nearby vehicle, and thus may be accurate keypointinformation on nearby vehicle 601 itself. Own vehicle 600 correctskeypoint information on the preceding vehicle in the point cloudobtained by own vehicle 600 by use of such keypoint information ofnearby vehicle 601. This enables own vehicle 600 to increase thematching accuracy at the time of self-location estimation.

The keypoint information of the preceding vehicle is, for example,three-dimensional point information that includes color information andcoordinates information. This allows for the use of the keypointinformation of the preceding vehicle independently of the type of thesensor of own vehicle 600, i.e., regardless of whether the sensor is alaser sensor or a stereo camera.

Own vehicle 600 may use the point cloud of a SWLD not only at the timeof transmission, but also at the time of calculating the accuracy ofself-location estimation. For example, when the sensor of own vehicle600 is an imaging device such as a stereo camera, own vehicle 600detects two-dimensional points on an image captured by the camera of ownvehicle 600, and uses such two-dimensional points to estimate theself-location. Own vehicle 600 also creates a point cloud of a nearbyobject at the same time of estimating the self-location. Own vehicle 600re-projects the three-dimensional points of the SWLD included in thepoint cloud onto the two-dimensional image, and evaluates the accuracyof self-location estimation on the basis of an error between thedetected points and the re-projected points on the two-dimensionalimage.

When the sensor of own vehicle 600 is a laser sensor such as a LIDAR,own vehicle 600 evaluates the accuracy of self-location estimation onthe basis of an error calculated by Interactive Closest Point algorithmby use of the SWLD of the created point cloud of and the SWLD of thethree-dimensional map.

When a communication state via a base station or a server is poor in,for example, a 5G environment, own vehicle 600 may obtain athree-dimensional map from nearby vehicle 601.

Also, own vehicle 600 may obtain information on a remote region thatcannot be obtained from a nearby vehicle, over inter-vehiclecommunication. For example, own vehicle 600 may obtain information on atraffic accident, etc. that has just occurred at a few hundred meters ora few kilometers away from own vehicle 600 from an oncoming vehicle overa passing communication, or by a relay system in which information issequentially passed to nearby vehicles. Here, the data format of thedata to be transmitted is transmitted as meta-information in an upperlayer of a dynamic three-dimensional map.

The result of detecting the surrounding conditions and the informationdetected by own vehicle 600 may be presented to the user via a UI. Thepresentation of such information is achieved, for example, bysuperimposing the information onto the screen of the car navigationsystem or the front window.

In the case of a vehicle not supporting self-driving but having thefunctionality of cruise control, the vehicle may identify a nearbyvehicle traveling in the self-driving mode, and track such nearbyvehicle.

Own vehicle 600 may switch the operation mode from the self-driving modeto the tracking mode to track a nearby vehicle, when failing to estimatethe self-location for the reason such as failing to obtain athree-dimensional map or having too large a number of occlusion regions.

Meanwhile, a vehicle to be tracked may include a UI which warns the userof that the vehicle is being tracked and by which the user can specifywhether to permit tracking. In this case, a system may be provided inwhich, for example, an advertisement is displayed to the vehicle that istracking and an incentive is given to the vehicle that is being tracked.

The information to be transmitted is basically a SWLD beingthree-dimensional data, but may also be information that is inaccordance with request settings set in own vehicle 600 or publicsettings set in a preceding vehicle. For example, the information to betransmitted may be a WLD being a dense point cloud, the detection resultof the surrounding conditions obtained by the preceding vehicle, or thebraking information of the preceding vehicle.

Own vehicle 600 may also receive a WLD, visualize the three-dimensionaldata of the WLD, and present such visualized three-dimensional data tothe driver by use of a GUI. In so doing, own vehicle 600 may present thethree-dimensional data in which information is color-coded, for example,so that the user can distinguish between the point cloud created by ownvehicle 600 and the received point cloud.

When presenting the information detected by own vehicle 600 and thedetection result of nearby vehicle 601 to the driver via the GUI, ownvehicle 600 may present the information in which information iscolor-coded, for example, so that the user can distinguish between theinformation detected by own vehicle 600 and the received detectionresult.

As described above, in three-dimensional data creation device 620according to the present embodiment, three-dimensional data creator 621creates first three-dimensional data 632 from sensor information 631detected by a sensor. Receiver 624 receives encoded three-dimensionaldata 634 that is obtained by encoding second three-dimensional data 635.Decoder 625 decodes received encoded three-dimensional data 634 toobtain second three-dimensional data 635. Merger 626 merges firstthree-dimensional data 632 with second three-dimensional data 635 tocreate third three-dimensional data 636.

Such three-dimensional data creation device 620 is capable of creatingdetailed third three-dimensional data 636 by use of created firstthree-dimensional data 632 and received second three-dimensional data635.

Also, merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635 to create third three-dimensional data 636that is denser than first three-dimensional data 632 and secondthree-dimensional data 635.

Second three-dimensional data 635 (e.g., SWLD) is three-dimensional datathat is generated by extracting, from fourth three-dimensional data(e.g., WLD), data having an amount of a feature greater than or equal tothe threshold.

Such three-dimensional data creation device 620 reduces the amount ofthree-dimensional data to be transmitted.

Three-dimensional data creation device 620 further includes searcher 623that searches for a transmission device that transmits encodedthree-dimensional data 634. Receiver 624 receives encodedthree-dimensional data 634 from the transmission device that has beensearched out.

Such three-dimensional data creation device 620 is, for example, capableof searching for a transmission device having necessarythree-dimensional data.

Such three-dimensional data creation device further includes requestrange determiner 622 that determines a request range that is a range ofa three-dimensional space, the three-dimensional of which is requested.Searcher 623 transmits request range information 633 indicating therequest range to the transmission device. Second three-dimensional data635 includes the three-dimensional data of the request range.

Such three-dimensional data creation device 620 is capable of receivingnecessary three-dimensional data, while reducing the amount ofthree-dimensional data to be transmitted.

Also, request range determiner 622 determines, as the request range, aspatial range that includes occlusion region 604 undetectable by thesensor.

Also, in three-dimensional data transmission device 640 according to thepresent embodiment, three-dimensional data creator 641 creates fifththree-dimensional data 652 from sensor information 651 detected by thesensor. Extractor 643 extracts part of fifth three-dimensional data 652to create sixth three-dimensional data 654. Encoder 644 encodes sixththree-dimensional data 654 to generate encoded three-dimensional data634. Transmitter 645 transmits encoded three-dimensional data 634.

Such three-dimensional data transmission device 640 is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

Also, three-dimensional data creator 641 creates sevenththree-dimensional data (e.g., WLD) from sensor information 651 detectedby the sensor, and extracts, from the seventh three-dimensional data,data having an amount of a feature greater than or equal to thethreshold, to create fifth three-dimensional data 652 (e.g., SWLD).

Such three-dimensional data creation device 640 reduces the amount ofthree-dimensional data to be transmitted.

Three-dimensional data transmission device 640 further includes receiver642 that receives, from the reception device, request range information633 indicating the request range that is the range of athree-dimensional space, the three-dimensional data of which isrequested. Extractor 643 extracts the three-dimensional data of therequest range from fifth three-dimensional data 652 to create sixththree-dimensional data 654. Transmitter 645 transmits encodedthree-dimensional data 634 to the reception device.

Such three-dimensional data transmission device 640 reduces the amountof three-dimensional data to be transmitted.

Embodiment 4

The present embodiment describes operations performed in abnormal caseswhen self-location estimation is performed on the basis of athree-dimensional map.

A three-dimensional map is expected to find its expanded use inself-driving of a vehicle and autonomous movement, etc. of a mobileobject such as a robot and a flying object (e.g., a drone). Examplemeans for enabling such autonomous movement include a method in which amobile object travels in accordance with a three-dimensional map, whileestimating its self-location on the map (self-location estimation).

The self-location estimation is enabled by matching a three-dimensionalmap with three-dimensional information on the surrounding of the ownvehicle (hereinafter referred to as self-detected three-dimensionaldata) obtained by a sensor equipped in the own vehicle, such as arangefinder (e.g., a LiDAR) and a stereo camera to estimate the locationof the own vehicle on the three-dimensional map.

As in the case of an HD map suggested by HERE Technologies, for example,a three-dimensional map may include not only a three-dimensional pointcloud, but also two-dimensional map data such as information on theshapes of roads and intersections, or information that changes inreal-time such as information on a traffic jam and an accident. Athree-dimensional map includes a plurality of layers such as layers ofthree-dimensional data, two-dimensional data, and meta-data that changesin real-time, from among which the device can obtain or refer to onlynecessary data.

Point cloud data may be a SWLD as described above, or may include pointgroup data that is different from keypoints. The transmission/receptionof point cloud data is basically carried out in one or more randomaccess units.

A method described below is used as a method of matching athree-dimensional map with self-detected three-dimensional data. Forexample, the device compares the shapes of the point groups in eachother's point clouds, and determines that portions having a high degreeof similarity among keypoints correspond to the same position. When thethree-dimensional map is formed by a SWLD, the device also performsmatching by comparing the keypoints that form the SWLD withthree-dimensional keypoints extracted from the self-detectedthree-dimensional data.

Here, to enable highly accurate self-location estimation, the followingneeds to be satisfied: (A) the three-dimensional map and theself-detected three-dimensional data have been already obtained; and (B)their accuracies satisfy a predetermined requirement. However, one of(A) and (B) cannot be satisfied in abnormal cases such as ones describedbelow.

1. A three-dimensional map is unobtainable over communication.

2. A three-dimensional map is not present, or a three-dimensional maphaving been obtained is corrupt.

3. A sensor of the own vehicle has trouble, or the accuracy of thegenerated self-detected three-dimensional data is inadequate due to badweather.

The following describes operations to cope with such abnormal cases. Thefollowing description illustrates an example case of a vehicle, but themethod described below is applicable to mobile objects on the whole thatare capable of autonomous movement, such as a robot and a drone.

The following describes the structure of the three-dimensionalinformation processing device and its operation according to the presentembodiment capable of coping with abnormal cases regarding athree-dimensional map or self-detected three-dimensional data. FIG. 34is a block diagram of an example structure of three-dimensionalinformation processing device 700 according to the present embodiment.FIG. 35 is a flowchart of a three-dimensional information processingmethod performed by three-dimensional information processing device 700.

Three-dimensional information processing device 700 is equipped, forexample, in a mobile object such as a car. As shown in FIG. 34,three-dimensional information processing device 700 includesthree-dimensional map obtainer 701, self-detected data obtainer 702,abnormal case judgment unit 703, coping operation determiner 704, andoperation controller 705.

Note that three-dimensional information processing device 700 mayinclude a non-illustrated two-dimensional or one-dimensional sensor thatdetects a structural object or a mobile object around the own vehicle,such as a camera capable of obtaining two-dimensional images and asensor for one-dimensional data utilizing ultrasonic or laser.Three-dimensional information processing device 700 may also include anon-illustrated communication unit that obtains a three-dimensional mapover a mobile communication network, such as 4G and 5G, or viainter-vehicle communication or road-to-vehicle communication.

As shown in FIG. 35, three-dimensional map obtainer 701 obtainsthree-dimensional map 711 of the surroundings of the traveling route(S701). For example, three-dimensional map obtainer 701 obtainsthree-dimensional map 711 over a mobile communication network, or viainter-vehicle communication or road-to-vehicle communication.

Next, self-detected data obtainer 702 obtains self-detectedthree-dimensional data 712 on the basis of sensor information (S702).For example, self-detected data obtainer 702 generates self-detectedthree-dimensional data 712 on the basis of the sensor informationobtained by a sensor equipped in the own vehicle.

Next, abnormal case judgment unit 703 conducts a predetermined check ofat least one of obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 to detect an abnormal case (S703). Stateddifferently, abnormal case judgment unit 703 judges whether at least oneof obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 is abnormal.

When the abnormal case is detected in step S703 (Yes in S704), copingoperation determiner 704 determines a coping operation to cope with suchabnormal case (S705). Next, operation controller 705 controls theoperation of each of the processing units necessary to perform thecoping operation (S706).

Meanwhile, when no abnormal case is detected in step S703 (No in S704),three-dimensional information processing device 700 terminates theprocess. Also, three-dimensional information processing device 700estimates the location of the vehicle equipped with three-dimensionalinformation processing device 700, using three-dimensional map 711 andself-detected three-dimensional data 712. Next, three-dimensionalinformation processing device 700 performs the automatic operation ofthe vehicle by use of the estimated location of the vehicle.

As described above, three-dimensional information processing device 700obtains, via a communication channel, map data (three-dimensional map711) that includes first three-dimensional position information. Thefirst three-dimensional position information includes, for example, aplurality of random access units, each of which is an assembly of atleast one subspace and is individually decodable, the at least onesubspace having three-dimensional coordinates information and serving asa unit in which each of the plurality of random access units is encoded.The first three-dimensional position information is, for example, data(SWLD) obtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.

Three-dimensional information processing device 700 also generatessecond three-dimensional position information (self-detectedthree-dimensional data 712) from information detected by a sensor.Three-dimensional information processing device 700 then judges whetherone of the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present.

Three-dimensional information processing device 700 determines a copingoperation to cope with the abnormality when one of the firstthree-dimensional position information and the second three-dimensionalposition information is judged to be abnormal. Three-dimensionalinformation processing device 700 then executes a control that isrequired to perform the coping operation.

This structure enables three-dimensional information processing device700 to detect an abnormality regarding one of the firstthree-dimensional position information and the second three-dimensionalposition information, and to perform a coping operation therefor.

The following describes coping operations used for the abnormal case 1in which three-dimensional map 711 is unobtainable via communication.

Three-dimensional map 711 is necessary to perform self-locationestimation, and thus the vehicle needs to obtain three-dimensional map711 via communication when not having obtained in advancethree-dimensional map 711 corresponding to the route to the destination.In some cases, however, the vehicle cannot obtain three-dimensional map711 of the traveling route due to a reason such as a congestedcommunication channel and a deteriorated environment of radio wavereception.

Abnormal case judgment unit 703 judges whether three-dimensional map 711of the entire section on the route to the destination or a sectionwithin a predetermined range from the current position has already beenobtained, and judges that the current condition applies to the abnormalcase 1 when three-dimensional map 711 has not been obtained yet. Stateddifferently, abnormal case judgment unit 703 judges whetherthree-dimensional map 711 (the first three-dimensional positioninformation) is obtainable via a communication channel, and judges thatthree-dimensional map 711 is abnormal when three-dimensional map 711 isunobtainable via a communication channel.

When the current condition is judged to be the abnormal case 1, copingoperation determiner 704 selects one of the two types of copingoperations: (1) continue the self-location estimation; and (2) terminatethe self-location estimation.

First, a specific example of the coping operation (1) continue theself-location estimation will be described. Three-dimensional map 711 ofthe route to the destination is necessary to continue the self-locationestimation.

For example, the vehicle identifies a place, within the range ofthree-dimensional map 711 having been obtained, in which the use of acommunication channel is possible. The vehicle moves to such identifiedplace, and obtains three-dimensional map 711. Here, the vehicle mayobtain the whole three-dimensional map 711 to the destination, or mayobtain three-dimensional map 711 on random access units within the upperlimit capacity of a storage of the own vehicle, such as a memory and anHDD.

Note that the vehicle may separately obtain communication conditions onthe route, and when the communication conditions on the route arepredicted to be poor, the vehicle may obtain in advancethree-dimensional map 711 of a section in which communication conditionsare predicted to be poor, before arriving at such section, or obtain inadvance three-dimensional map 711 of the maximum range obtainable.Stated differently, three-dimensional information processing device 700predicts whether the vehicle will enter an area in which communicationconditions are poor. When the vehicle is predicted to enter an area inwhich communication conditions are poor, three-dimensional informationprocessing device 700 obtains three-dimensional map 711 before thevehicle enters such area.

Alternatively, the vehicle may identify a random access unit that formsthe minimum three-dimensional map 711, the range of which is narrowerthan that of the normal times, required to estimate the location of thevehicle on the route, and receive a random access unit having beenidentified. Stated differently, three-dimensional information processingdevice 700 may obtain, via a communication channel, thirdthree-dimensional position information having a narrower range than therange of the first three-dimensional position information, whenthree-dimensional map 711 (the first three-dimensional positioninformation) is unobtainable via the communication channel.

Also, when being unable to access a server that distributesthree-dimensional map 711, the vehicle may obtain three-dimensional map711 from a mobile object that has already obtained three-dimensional map711 of the route to the destination and that is capable of communicatingwith the own vehicle, such as another vehicle traveling around the ownvehicle.

Next, a specific example of the coping operation to terminate theself-location estimation will be described. Three-dimensional map 711 ofthe route to the destination is unnecessary in this case.

For example, the vehicle notifies the driver of that the vehicle cannotmaintain the functionally of automatic operation, etc. that is performedon the basis of the self-location estimation, and shifts the operationmode to a manual mode in which the driver operates the vehicle.

Automatic operation is typically carried out when self-locationestimation is performed, although there may be a difference in the levelof automatic operation in accordance with the degree of humaninvolvement. Meanwhile, the estimated location of the vehicle can alsobe used as navigation information, etc. when the vehicle is operated bya human, and thus the estimated location of the vehicle is notnecessarily used for automatic operation.

Also, when being unable to use a communication channel that the vehicleusually uses, such as a mobile communication network (e.g., 4G and 5G),the vehicle checks whether three-dimensional map 711 is obtainable viaanother communication channel, such as road-to-vehicle Wi-Fi (registeredtrademark) or millimeter-wave communication, or inter-vehiclecommunication, and switches to one of these communication channels viawhich three-dimensional map 711 is obtainable.

When being unable to obtain three-dimensional map 711, the vehicle mayobtain a two-dimensional map to continue automatic operation by use ofsuch two-dimensional map and self-detected three-dimensional data 712.Stated differently, when being unable to obtain three-dimensional map711 via a communication channel, three-dimensional informationprocessing device 700 may obtain, via a communication channel, map datathat includes two-dimensional position information (a two-dimensionalmap) to estimate the location of the vehicle by use of thetwo-dimensional position information and self-detected three-dimensionaldata 712.

More specifically, the vehicle uses the two-dimensional map andself-detected three-dimensional data 712 to estimate its self-location,and uses self-detected three-dimensional data 712 to detect a vehicle, apedestrian, an obstacle, etc. around the own vehicle.

Here, the map data such as an HD map is capable of including, togetherwith three-dimensional map 711 formed by a three-dimensional pointcloud: two-dimensional map data (a two-dimensional map); simplified mapdata obtained by extracting, from the two-dimensional map data,characteristic information such as a road shape and an intersection; andmeta-data representing real-time information such as a traffic jam, anaccident, and a roadwork. For example, the map data has a layerstructure in which three-dimensional data (three-dimensional map 711),two-dimensional data (a two-dimensional map), and meta-data are disposedfrom the bottom layer in the stated order.

Here, the two-dimensional data is smaller in data size than thethree-dimensional data. It may be thus possible for the vehicle toobtain the two-dimensional map even when communication conditions arepoor.

Alternatively, the vehicle can collectively obtain the two-dimensionalmap of a wide range in advance when in a section in which communicationconditions are good. The vehicle thus may receive a layer including thetwo-dimensional map without receiving three-dimensional map 711, whencommunication conditions are poor and it is difficult to obtainthree-dimensional map 711. Note that the meta-data is small in datasize, and thus the vehicle receives the meta-data without fail,regardless, for example, of communication conditions.

Example methods of self-location estimation using the two-dimensionalmap and self-detected three-dimensional data 712 include two methodsdescribed below.

A first method is to perform matching of two-dimensional features. Morespecifically, the vehicle extracts two-dimensional features fromself-detected three-dimensional data 712 to perform matching between theextracted two-dimensional features and the two-dimensional map.

For example, the vehicle projects self-detected three-dimensional data712 onto the same plane as that of the two-dimensional map, and matchesthe resulting two-dimensional data with the two-dimensional map. Suchmatching is performed by use of features of the two-dimensional imagesextracted from the two-dimensional data and the two-dimensional map.

When three-dimensional map 711 includes a SWLD, two-dimensional featureson the same plane as that of the two-dimensional map may be stored inthree-dimensional map 711 together with three-dimensional features ofkeypoints in a three-dimensional space. For example, identificationinformation is assigned to two-dimensional features. Alternatively,two-dimensional features are stored in a layer different from the layersof the three-dimensional data and the two-dimensional map, and thevehicle obtains data of the two-dimensional features together with thetwo-dimensional map.

When the two-dimensional map shows, on the same map, information onpositions having different heights from the ground (i.e., positions thatare not on the same plane), such as a white line inside a road, aguardrail, and a building, the vehicle extracts features from data on aplurality of heights in self-detected three-dimensional data 712.

Also, information indicating a correspondence between keypoints on thetwo-dimensional map and keypoints on three-dimensional map 711 may bestored as meta-information of the map data.

A second method is to perform matching of three-dimensional features.More specifically, the vehicle obtains three-dimensional featurescorresponding to keypoints on the two-dimensional map, and matches theobtained three-dimensional features with three-dimensional features inself-detected three-dimensional data 712.

More specifically, three-dimensional features corresponding to keypointson the two-dimensional map are stored in the map data. The vehicleobtains such three-dimensional features when obtaining thetwo-dimensional map. Note that when three-dimensional map 711 includes aSWLD, information is provided that identifies those keypoints, among thekeypoints in the SWLD, that correspond to keypoints on thetwo-dimensional map. Such identification information enables the vehicleto determine three-dimensional features that should be obtained togetherwith the two-dimensional map. In this case, the representation oftwo-dimensional positions is only required, and thus the amount of datacan be reduced compared to the case of representing three-dimensionalpositions.

The use of the two-dimensional map to perform self-location estimationdecreases the accuracy of the self-location estimation compared to thecase of using three-dimensional map 711. For this reason, the vehiclejudges whether the vehicle can continue automatic operation by use ofthe location having decreased estimation accuracy, and may continueautomatic operation only when judging that the vehicle can continueautomatic operation.

Whether the vehicle can continue automatic operation is affected by anenvironment in which the vehicle is traveling such as whether the roadon which the vehicle is traveling is a road in an urban area or a roadaccessed less often by another vehicle or a pedestrian, such as anexpressway, and the width of a road or the degree of congestion of aroad (the density of vehicles or pedestrians). It is also possible todispose, in a premise of a business place, a town, or inside a building,markers recognized by a senor such as a camera. Since a two-dimensionalsensor is capable of highly accurate recognition of such markers in thespecified areas, highly accurate self-location estimation is enabled by,for example, incorporating information on the positions of the markersinto the two-dimensional map.

Also, by incorporating, into the map, identification informationindicating whether each area corresponds to a specified area, forexample, the vehicle can judge whether such vehicle is currently in aspecified area. When in a specified area, the vehicle judges that thevehicle can continue automatic operation. As described above, thevehicle may judge whether the vehicle can continue automatic operationon the basis of the accuracy of self-location estimation that uses thetwo-dimensional map or an environment in which the vehicle is traveling.

As described above, three-dimensional information processing device 700judges whether to perform automatic operation that utilizes the locationof the vehicle having been estimated by use of the two-dimensional mapand self-detected three-dimensional data 712, on the basis of anenvironment in which the vehicle is traveling (a traveling environmentof the mobile object).

Alternatively, the vehicle may not judge whether the vehicle cancontinue automatic operation, but may switch levels (modes) of automaticoperation in accordance with the accuracy of self-location estimation orthe traveling environment of the vehicle. Here, to switch levels (modes)of automatic operation means, for example, to limit the speed, increasethe degree of driver operation (lower the automatic level of automaticoperation), switch to a mode in which the vehicle obtains information onthe operation of a preceding vehicle to refer to it for its ownoperation, switch to a mode in which the vehicle obtains information onthe operation of a vehicle heading for the same destination to use itfor automatic operation, etc.

The map may also include information, associated with the positioninformation, indicating a recommendation level of automatic operationfor the case where the two-dimensional map is used for self-locationestimation. The recommendation level may be meta-data that dynamicallychanges in accordance with the volume of traffic, etc. This enables thevehicle to determine a level only by obtaining information from the mapwithout needing to judge a level every time an environment, etc. aroundthe vehicle changes. Also, it is possible to maintain a constant levelof automatic operation of individual vehicles by such plurality ofvehicles referring to the same map. Note that the recommendation levelmay not be “recommendation,” and thus such level may be a mandatorylevel that should be abided by.

The vehicle may also switch the level of automatic operation inaccordance with the presence or absence of the driver (whether thevehicle is manned or unmanned). For example, the vehicle lowers thelevel of automatic operation when the vehicle is manned, and terminatesautomatic operation when unmanned. The vehicle may recognize apedestrian, a vehicle, and a traffic sign around the vehicle todetermine a position where the vehicle can stop safely. Alternatively,the map may include position information indicating positions where thevehicle can stop safely, and the vehicle refers to such positioninformation to determine a position where the vehicle can stop safely.

The following describes coping operations to cope with the abnormal case2 in which three-dimensional map 711 is not present, orthree-dimensional map 711 having been obtained is corrupt.

Abnormal case judgment unit 703 checks whether the current conditionapplies to one of; (1) three-dimensional map 711 of part or the entiretyof the section on the route to the destination not being present in adistribution server, etc. to which the vehicle accesses, and thusunobtainable; and (2) part or the entirety of obtained three-dimensionalmap 711 being corrupt. When one of these cases applies, the vehiclejudges that the current condition applies to the abnormal case 2. Stateddifferently, abnormal case judgment unit 703 judges whether the data ofthree-dimensional map 711 has integrity, and judges thatthree-dimensional map 711 is abnormal when the data of three-dimensionalmap 711 has no integrity.

When the current condition is judged to apply to the abnormal case 2,coping operations described below are performed. First, an examplecoping operation for the case where (1) three-dimensional map 711 isunobtainable will be described.

For example, the vehicle sets a route that avoids a section,three-dimensional map 711 of which is not present.

When being unable to set an alternative route for a reason that analternative route is not present, an alternative route is present butits distance is substantially longer, or etc., the vehicle sets a routethat includes a section, three-dimensional map 711 of which is notpresent. When in such section, the vehicle notifies the driver of thenecessity to switch to another operation mode, and switches theoperation mode to the manual mode.

When the current condition applies to (2) in which part or the entiretyof obtained three-dimensional map 711 is corrupt, a coping operationdescribed below is performed.

The vehicle identifies a corrupted portion of three-dimensional map 711,requests for the data of such corrupted portion via communication,obtains the data of the corrupted portion, and updates three-dimensionalmap 711 using the obtained data. In so doing, the vehicle may specifythe corrupted portion on the basis of position information inthree-dimensional map 711, such as absolute coordinates and relativecoordinates, or may specify the corrupted portion by an index number,etc. assigned to a random access unit that forms the corrupted portion.In such case, the vehicle replaces the random access unit including thecorrupted portion with a random access unit having been obtained.

The following describes coping operations to cope with the abnormal case3 in which the vehicle fails to generate self-detected three-dimensionaldata 712 due to trouble of a sensor of the own vehicle or bad weather.

Abnormal case judgment unit 703 checks whether an error in generatedself-detected three-dimensional data 712 falls within an acceptablerange, and judges that the current condition applies to the abnormalcase 3 when such error is beyond the acceptable range. Stateddifferently, abnormal case judgment unit 703 judges whether the dataaccuracy of generated self-detected three-dimensional data 712 is higherthan or equal to the reference value, and judges that self-detectedthree-dimensional data 712 is abnormal when the data accuracy ofgenerated self-detected three-dimensional data 712 is not higher than orequal to the reference value.

A method described below is used to check whether an error in generatedself-detected three-dimensional data 712 is within the acceptable range.

A spatial resolution of self-detected three-dimensional data 712 whenthe own vehicle is in normal operation is determined in advance on thebasis of the resolutions in the depth and scanning directions of athree-dimensional sensor of the own vehicle, such as a rangefinder and astereo camera, or on the basis of the density of generatable pointgroups. Also, the vehicle obtains the spatial resolution ofthree-dimensional map 711 from meta-information, etc. included inthree-dimensional map 711.

The vehicle uses the spatial resolutions of self-detectedthree-dimensional data 712 and three-dimensional map 711 to estimate areference value used to specify a matching error in matchingself-detected three-dimensional data 712 with three-dimensional map 711on the basis of three-dimensional features, etc. Used as the matchingerror is an error in three-dimensional features of the respectivekeypoints, statistics such as the mean value of errors inthree-dimensional features among a plurality of keypoints, or an errorin spatial distances among a plurality of keypoints. The acceptablerange of a deviation from the reference value is set in advance.

The vehicle judges that the current condition applies to the abnormalcase 3 when the matching error between self-detected three-dimensionaldata 712 generated before or in the middle of traveling andthree-dimensional map 711 is beyond the acceptable range.

Alternatively, the vehicle may use a test pattern having a knownthree-dimensional shape for accuracy check to obtain, before the startof traveling, for example, self-detected three-dimensional data 712corresponding to such test pattern, and judge whether the currentcondition applies to the abnormal case 3 on the basis of whether a shapeerror is within the acceptable range.

For example, the vehicle makes the above judgment before every start oftraveling. Alternatively, the vehicle makes the above judgment at aconstant time interval while traveling, thereby obtaining time-seriesvariations in the matching error. When the matching error shows anincreasing trend, the vehicle may judge that the current conditionapplies to the abnormal case 3 even when the error is within theacceptable range. Also, when an abnormality can be predicted on thebasis of the time-series variations, the vehicle may notify the user ofthat an abnormality is predicted by displaying, for example, a messagethat prompts the user for inspection or repair. The vehicle maydiscriminate between an abnormality attributable to a transient factorsuch as bad weather and an abnormality attributable to sensor trouble onthe basis of time-series variations, and notify the user only of anabnormality attributable to sensor trouble.

When the current condition is judged to be the abnormal case 3, thevehicle performs one, or selective ones of the following three types ofcoping operations: (1) operate an alternative emergency sensor (rescuemode); (2) switch to another operation mode; and (3) calibrate theoperation of a three-dimensional sensor.

First, the coping operation (1) operate an alternative emergency sensorwill be described. The vehicle operates an alternative emergency sensorthat is different from a three-dimensional sensor used for normaloperation. Stated differently, when the accuracy of generatedself-detected three-dimensional data 712 is not higher than or equal tothe reference value, three-dimensional information processing device 700generates self-detected three-dimensional data 712 (fourththree-dimensional position information) from information detected by thealternative sensor that is different from a usual sensor.

More specifically, when obtaining self-detected three-dimensional data712 in a combined use of a plurality of cameras or LiDARs, the vehicleidentifies a malfunctioning sensor, on the basis of a direction, etc. inwhich the matching error of self-detected three-dimensional data 712 isbeyond the acceptable range. Subsequently, the vehicle operates analternative sensor corresponding to such malfunctioning sensor.

The alternative sensor may be a three-dimensional sensor, a cameracapable of obtaining two-dimensional images, or a one-dimensional sensorsuch as an ultrasonic sensor. The use of an alternative sensor otherthan a three-dimensional sensor can result in a decrease in the accuracyof self-location estimation or the failure to perform self-locationestimation. The vehicle thus may switch automatic operation modesdepending on the type of an alternative sensor.

When an alternative sensor is a three-dimensional sensor, for example,the vehicle maintains the current automatic operation mode. When analternative sensor is a two-dimensional sensor, the vehicle switches theoperation mode from the full automatic operation mode to thesemi-automatic operation mode that requires human operation. When analternative sensor is a one-dimensional sensor, the vehicle switches theoperation mode to the manual mode that performs no automatic brakingcontrol.

Alternatively, the vehicle may switch automatic operation modes on thebasis of a traveling environment. When an alternative sensor is atwo-dimensional sensor, for example, the vehicle maintains the fullautomatic operation mode when traveling on an expressway, and switchesthe operation mode to the semi-automatic operation mode when travelingin an urban area.

Also, even when no alternative sensor is available, the vehicle maycontinue the self-location estimation so long as a sufficient number ofkeypoints are obtainable only by normally operating sensors. Sincedetection cannot work in a specific direction in this case, the vehicleswitches the current operation mode to the semi-automatic operation modeor the manual mode.

Next, the coping operation (2) switch to another operation mode will bedescribed. The vehicle switches the current operation mode from theautomatic operation mode to the manual mode. The vehicle may continueautomatic operation until arriving at the shoulder of the road, oranother place where the vehicle can stop safely, and then stop there.The vehicle may switch the current operation mode to the manual modeafter stopping. As described above, three-dimensional informationprocessing device 700 switches the automatic operation mode to anothermode when the accuracy of generated self-detected three-dimensional data712 is not higher than or equal to the reference value.

Next, the coping operation (3) calibrate the operation of athree-dimensional sensor will be described. The vehicle identifies amalfunctioning three-dimensional sensor from a direction, etc. in whicha matching error is occurring, and calibrates the identified sensor.More specifically, when a plurality of LiDARs or cameras are used assensors, an overlapped portion is included in a three-dimensional spacereconstructed by each of the sensors. Stated differently, datacorresponding to such overlapped portion is obtained by a plurality ofsensors. However, a properly operating sensor and a malfunctioningsensor obtain different three-dimensional point group data correspondingto the overlapped portion. The vehicle thus calibrates the origin pointof the LiDAR or adjusts the operation for a predetermined part such asone responsible for camera exposure and focus so that the malfunctioningsensor can obtain the data of a three-dimensional point group equivalentto that obtained by a properly operating sensor.

When the matching error falls within the acceptable range as a result ofsuch adjustment, the vehicle maintains the previous operation mode.Meanwhile, when the matching accuracy fails to fall within theacceptable range after such adjustment, the vehicle performs one of theabove coping operations: (1) operate an alternative emergency sensor;and (2) switch to another operation mode.

As described above, three-dimensional information processing device 700calibrates a sensor operation when the data accuracy of generatedself-detected three-dimensional data 712 is not higher than or equal tothe reference value.

The following describes a method of selecting a cooping operation. Acoping operation may be selected by the user such as a driver, or may beautomatically selected by the vehicle without user's involvement.

The vehicle may switch controls in accordance with whether the driver isonboard. For example, when the driver is onboard, the vehicleprioritizes the manual mode. Meanwhile, when the driver is not onboard,the vehicle prioritizes the mode to move to a safe place and stop.

Three-dimensional map 711 may include information indicating places tostop as meta-information. Alternatively, the vehicle may issue, to aservice firm that manages operation information on a self-drivingvehicle, a request to send a reply indicating a place to stop, therebyobtaining information on the place to stop.

Also, when the vehicle travels on a fixed route, for example, theoperation mode of the vehicle may be switched to a mode in which anoperator controls the operation of the vehicle via a communicationchannel. It is highly dangerous when there is a failure in the functionof self-location estimation especially when the vehicle is traveling inthe full automatic operation mode. When any abnormal case is detected ora detected abnormality cannot be fixed, the vehicle notifies, via acommunication channel, the service firm that manages the operationinformation of the occurrence of the abnormality. Such service firm maynotify vehicles, etc. traveling around such vehicle in trouble of thepresence of a vehicle having an abnormality or that they should clear anearby space for the vehicle to stop.

The vehicle may also travel at a decreased speed compared to normaltimes when any abnormal case has been detected.

When the vehicle is a self-driving vehicle from a vehicle dispatchservice such as a taxi, and an abnormal case occurs in such vehicle, thevehicle contacts an operation control center, and then stops at a safeplace. The firm of the vehicle dispatch service dispatches analternative vehicle. The user of such vehicle dispatch service mayoperate the vehicle instead. In these cases, fee discount or benefitpoints may be provided in combination.

In the description of the coping operations for the abnormal case 1,self-location estimation is performed on the basis of thetwo-dimensional map, but self-location estimation may be performed alsoin normal times by use of the two-dimensional map. FIG. 36 is aflowchart of self-location estimation processes performed in such case.

First, the vehicle obtains three-dimensional map 711 of the surroundingsof the traveling route (S711). The vehicle then obtains self-detectedthree-dimensional data 712 on the basis of sensor information (S712).

Next, the vehicle judges whether three-dimensional map 711 is necessaryfor self-location estimation (S713). More specifically, the vehiclejudges whether three-dimensional map 711 is necessary on the basis ofthe accuracy of its location having been estimated by use of thetwo-dimensional map and the traveling environment. For example, a methodsimilar to the above-described coping operations for the abnormal case 1is used.

When judging that three-dimensional map 711 is not necessary (No inS714), the vehicle obtains a two-dimensional map (S715). In so doing,the vehicle may obtain additional information together that is mentionedwhen the coping operations for the abnormal case 1 have been described.Alternatively, the vehicle may generate a two-dimensional map fromthree-dimensional map 711. For example, the vehicle may generate atwo-dimensional map by cutting out any plane from three-dimensional map711.

Next, the vehicle performs self-location estimation by use ofself-detected three-dimensional data 712 and the two-dimensional map(S716). Note that a method of self-location estimation by use of atwo-dimensional map is similar to the above-described coping operationsfor the abnormal case 1.

Meanwhile, when judging that three-dimensional map 711 is necessary (Yesin S714), the vehicle obtains three-dimensional map 711 (S717). Then,the vehicle performs self-location estimation by use of self-detectedthree-dimensional data 712 and three-dimensional map 711 (S718).

Note that the vehicle may selectively decide on which one of thetwo-dimensional map and three-dimensional map 711 to basically use, inaccordance with a speed supported by a communication device of the ownvehicle or conditions of a communication channel. For example, acommunication speed that is required to travel while receivingthree-dimensional map 711 is set in advance, and the vehicle maybasically use the two-dimensional map when the communication speed atthe time of traveling is less than or equal to the such set value, andbasically use three-dimensional map 711 when the communication speed atthe time of traveling is greater than the set value. Note that thevehicle may basically use the two-dimensional map without judging whichone of the two-dimensional map and the three-dimensional map to use.

Embodiment 5

The present embodiment describes a method, etc. of transmittingthree-dimensional data to a following vehicle. FIG. 37 is a diagramshowing an exemplary space, three-dimensional data of which is to betransmitted to a following vehicle, etc.

Vehicle 801 transmits, at the time interval of Δt, three-dimensionaldata, such as a point cloud (a point group) included in a rectangularsolid space 802, having width W, height H, and depth D, located ahead ofvehicle 801 and distanced by distance L from vehicle 801, to acloud-based traffic monitoring system that monitors road situations or afollowing vehicle.

When a change has occurred in the three-dimensional data of a space thatis included in space 802 already transmitted in the past, due to avehicle or a person entering space 802 from outside, for example,vehicle 801 also transmits three-dimensional data of the space in whichsuch change has occurred.

Although FIG. 37 illustrates an example in which space 802 has arectangular solid shape, space 802 is not necessarily a rectangularsolid so long as space 802 includes a space on the forward road that ishidden from view of a following vehicle.

Distance L may be set to a distance that allows the following vehiclehaving received the three-dimensional data to stop safely. For example,set as distance L is the sum of; a distance traveled by the followingvehicle while receiving the three-dimensional data; a distance traveledby the following vehicle until the following vehicle starts speedreduction in accordance with the received data; and a distance requiredby the following vehicle to stop safely after starting speed reduction.These distances vary in accordance with the speed, and thus distance Lmay vary in accordance with speed V of the vehicle, just like L=axV+b (aand b are constants).

Width W is set to a value that is at least greater than the width of thelane on which vehicle 801 is traveling. Width W may also be set to asize that includes an adjacent space such as right and left lanes and aside strip.

Depth D may have a fixed value, but may vary in accordance with speed Vof the vehicle, just like D=c×V+d (c and d are constants). Also, D thatis set to satisfy D>V×Δt enables the overlap of a space to betransmitted and a space transmitted in the past. This enables vehicle801 to transmit a space on the traveling road to the following vehicle,etc. completely and more reliably. As described above, vehicle 801transmits three-dimensional data of a limited space that is useful tothe following vehicle, thereby effectively reducing the amount of thethree-dimensional data to be transmitted and achieving low-latency,low-cost communication.

The following describes the structure of three-dimensional data creationdevice 810 according to the present embodiment. FIG. 38 is a blockdiagram of an exemplary structure of three-dimensional data creationdevice 810 according to the present embodiment. Such three-dimensionaldata creation device 810 is equipped, for example, in vehicle 801.Three-dimensional data creation device 810 transmits and receivesthree-dimensional data to and from an external cloud-based trafficmonitoring system, a preceding vehicle, or a following vehicle, andcreates and stores three-dimensional data.

Three-dimensional data creation device 810 includes data receiver 811,communication unit 812, reception controller 813, format converter 814,a plurality of sensors 815, three-dimensional data creator 816,three-dimensional data synthesizer 817, three-dimensional data storage818, communication unit 819, transmission controller 820, formatconverter 821, and data transmitter 822.

Data receiver 811 receives three-dimensional data 831 from a cloud-basedtraffic monitoring system or a preceding vehicle. Three-dimensional data831 includes, for example, information on a region undetectable bysensors 815 of the own vehicle, such as a point cloud, visible lightvideo, depth information, sensor position information, and speedinformation.

Communication unit 812 communicates with the cloud-based trafficmonitoring system or the preceding vehicle to transmit a datatransmission request, etc. to the cloud-based traffic monitoring systemor the preceding vehicle.

Reception controller 813 exchanges information, such as information onsupported formats, with a communications partner via communication unit812 to establish communication with the communications partner.

Format converter 814 applies format conversion, etc. onthree-dimensional data 831 received by data receiver 811 to generatethree-dimensional data 832. Format converter 814 also decompresses ordecodes three-dimensional data 831 when three-dimensional data 831 iscompressed or encoded.

A plurality of sensors 815 are a group of sensors, such as visible lightcameras and infrared cameras, that obtain information on the outside ofvehicle 801 and generate sensor information 833. Sensor information 833is, for example, three-dimensional data such as a point cloud (pointgroup data), when sensors 815 are laser sensors such as LIDARs. Notethat a single sensor may serve as a plurality of sensors 815.

Three-dimensional data creator 816 generates three-dimensional data 834from sensor information 833. Three-dimensional data 834 includes, forexample, information such as a point cloud, visible light video, depthinformation, sensor position information, and speed information.

Three-dimensional data synthesizer 817 synthesizes three-dimensionaldata 834 created on the basis of sensor information 833 of the ownvehicle with three-dimensional data 832 created by the cloud-basedtraffic monitoring system or the preceding vehicle, etc., therebyforming three-dimensional data 835 of a space that includes the spaceahead of the preceding vehicle undetectable by sensors 815 of the ownvehicle.

Three-dimensional data storage 818 stores generated three-dimensionaldata 835, etc.

Communication unit 819 communicates with the cloud-based trafficmonitoring system or the following vehicle to transmit a datatransmission request, etc. to the cloud-based traffic monitoring systemor the following vehicle.

Transmission controller 820 exchanges information such as information onsupported formats with a communications partner via communication unit819 to establish communication with the communications partner.Transmission controller 820 also determines a transmission region, whichis a space of the three-dimensional data to be transmitted, on the basisof three-dimensional data formation information on three-dimensionaldata 832 generated by three-dimensional data synthesizer 817 and thedata transmission request from the communications partner.

More specifically, transmission controller 820 determines a transmissionregion that includes the space ahead of the own vehicle undetectable bya sensor of the following vehicle, in response to the data transmissionrequest from the cloud-based traffic monitoring system or the followingvehicle. Transmission controller 820 judges, for example, whether aspace is transmittable or whether the already transmitted space includesan update, on the basis of the three-dimensional data formationinformation to determine a transmission region. For example,transmission controller 820 determines, as a transmission region, aregion that is: a region specified by the data transmission request; anda region, corresponding three-dimensional data 835 of which is present.Transmission controller 820 then notifies format converter 821 of theformat supported by the communications partner and the transmissionregion.

Of three-dimensional data 835 stored in three-dimensional data storage818, format converter 821 converts three-dimensional data 836 of thetransmission region into the format supported by the receiver end togenerate three-dimensional data 837. Note that format converter 821 maycompress or encode three-dimensional data 837 to reduce the data amount.

Data transmitter 822 transmits three-dimensional data 837 to thecloud-based traffic monitoring system or the following vehicle. Suchthree-dimensional data 837 includes, for example, information on a blindspot, which is a region hidden from view of the following vehicle, suchas a point cloud ahead of the own vehicle, visible light video, depthinformation, and sensor position information.

Note that an example has been described in which format converter 814and format converter 821 perform format conversion, etc., but formatconversion may not be performed.

With the above structure, three-dimensional data creation device 810obtains, from an external device, three-dimensional data 831 of a regionundetectable by sensors 815 of the own vehicle, and synthesizesthree-dimensional data 831 with three-dimensional data 834 that is basedon sensor information 833 detected by sensors 815 of the own vehicle,thereby generating three-dimensional data 835. Three-dimensional datacreation device 810 is thus capable of generating three-dimensional dataof a range undetectable by sensors 815 of the own vehicle.

Three-dimensional data creation device 810 is also capable oftransmitting, to the cloud-based traffic monitoring system or thefollowing vehicle, etc., three-dimensional data of a space that includesthe space ahead of the own vehicle undetectable by a sensor of thefollowing vehicle, in response to the data transmission request from thecloud-based traffic monitoring system or the following vehicle.

The following describes the steps performed by three-dimensional datacreation device 810 of transmitting three-dimensional data to afollowing vehicle. FIG. 39 is a flowchart showing exemplary stepsperformed by three-dimensional data creation device 810 of transmittingthree-dimensional data to a cloud-based traffic monitoring system or afollowing vehicle.

First, three-dimensional data creation device 810 generates and updatesthree-dimensional data 835 of a space that includes space 802 on theroad ahead of own vehicle 801 (S801). More specifically,three-dimensional data creation device 810 synthesizes three-dimensionaldata 834 created on the basis of sensor information 833 of own vehicle801 with three-dimensional data 831 created by the cloud-based trafficmonitoring system or the preceding vehicle, etc., for example, therebyforming three-dimensional data 835 of a space that also includes thespace ahead of the preceding vehicle undetectable by sensors 815 of theown vehicle.

Three-dimensional data creation device 810 then judges whether anychange has occurred in three-dimensional data 835 of the space includedin the space already transmitted (S802).

When a change has occurred in three-dimensional data 835 of the spaceincluded in the space already transmitted due to, for example, a vehicleor a person entering such space from outside (Yes in S802),three-dimensional data creation device 810 transmits, to the cloud-basedtraffic monitoring system or the following vehicle, thethree-dimensional data that includes three-dimensional data 835 of thespace in which the change has occurred (S803).

Three-dimensional data creation device 810 may transmitthree-dimensional data in which a change has occurred, at the sametiming of transmitting three-dimensional data that is transmitted at apredetermined time interval, or may transmit three-dimensional data inwhich a change has occurred soon after the detection of such change.Stated differently, three-dimensional data creation device 810 mayprioritize the transmission of three-dimensional data of the space inwhich a change has occurred to the transmission of three-dimensionaldata that is transmitted at a predetermined time interval.

Also, three-dimensional data creation device 810 may transmit, asthree-dimensional data of a space in which a change has occurred, thewhole three-dimensional data of the space in which such change hasoccurred, or may transmit only a difference in the three-dimensionaldata (e.g., information on three-dimensional points that have appearedor vanished, or information on the displacement of three-dimensionalpoints).

Three-dimensional data creation device 810 may also transmit, to thefollowing vehicle, meta-data on a risk avoidance behavior of the ownvehicle such as hard breaking warning, before transmittingthree-dimensional data of the space in which a change has occurred. Thisenables the following vehicle to recognize at an early stage that thepreceding vehicle is to perform hard braking, etc., and thus to startperforming a risk avoidance behavior at an early stage such as speedreduction.

When no change has occurred in three-dimensional data 835 of the spaceincluded in the space already transmitted (No in S802), or after stepS803, three-dimensional data creation device 810 transmits, to thecloud-based traffic monitoring system or the following vehicle,three-dimensional data of the space included in the space having apredetermined shape and located ahead of own vehicle 801 by distance L(S804).

The processes of step S801 through step S804 are repeated, for exampleat a predetermined time interval.

When three-dimensional data 835 of the current space 802 to betransmitted includes no difference from the three-dimensional map,three-dimensional data creation device 810 may not transmitthree-dimensional data 837 of space 802.

FIG. 40 is a flowchart of the operation performed by three-dimensionaldata creation device 810 in such case.

First, three-dimensional data creation device 810 generates and updatesthree-dimensional data 835 of a space that includes space 802 on theroad ahead of own vehicle 801 (S811).

Three-dimensional data creation device 810 then judges whetherthree-dimensional data 835 of space 802 that has been generated includesan update from the three-dimensional map (S812). Stated differently,three-dimensional data creation device 810 judges whetherthree-dimensional data 835 of space 802 that has been generated isdifferent from the three-dimensional map. Here, the three-dimensionalmap is three-dimensional map information managed by a device on theinfrastructure side such as a cloud-based traffic monitoring system.Such three-dimensional map is obtained, for example, asthree-dimensional data 831.

When an update is included (Yes in S812), three-dimensional datacreation device 810 transmits three-dimensional data of the spaceincluded in space 802 to the cloud-based traffic monitoring system orthe following vehicle just like the above case (S813).

Meanwhile, when no update is included (No in S812), three-dimensionaldata creation device 810 does not transmit three-dimensional data of thespace included in space 802 to the cloud-based traffic monitoring systemor the following vehicle (S814). Note that three-dimensional datacreation device 810 may set the volume of space 802 to zero, therebycontrolling the three-dimensional data of space 802 not to betransmitted. Alternatively, three-dimensional data creation device 810may transmit information indicating that space 802 includes no update tothe cloud-based traffic monitoring system or the following vehicle.

As described above, data is not transmitted when, for example, noobstacle is present on the road and thus no difference is presentbetween three-dimensional data 835 that has been generated and thethree-dimensional map of on infrastructure side. This prevents thetransmission of unnecessary data.

Note that the above description illustrates a non-limited example inwhich three-dimensional data creation device 810 is equipped in avehicle, and thus three-dimensional data creation device 810 may beequipped in any mobile object.

As described above, three-dimensional data creation device 810 accordingto the present embodiment is equipped in a mobile object that includessensors 815 and a communication unit (data receiver 811, or datatransmitter 822, etc.) that transmits and receives three-dimensionaldata to and from an external device. Three-dimensional data creationdevice 810 creates three-dimensional data 835 (second three-dimensionaldata) on the basis of sensor information 833 detected by sensors 815 andthree-dimensional data 831 (first three-dimensional data) received bydata receiver 811. Three-dimensional data creation device 810 transmitsthree-dimensional data 837 that is part of three-dimensional data 835 tothe external device.

Such three-dimensional data creation device 810 is capable of generatingthree-dimensional data of a range undetectable by the own vehicle.Three-dimensional data creation device 810 is also capable oftransmitting, to another vehicle, etc., three-dimensional data of arange undetectable by such another vehicle, etc.

Also, three-dimensional data creation device 810 repeats the creation ofthree-dimensional data 835 and the transmission of three-dimensionaldata 837 at a predetermined time interval. Three-dimensional data 837 isthree-dimensional data of small space 802 having a predetermined sizeand located predetermined distance L ahead of the current position ofvehicle 801 in a traveling direction of vehicle 801.

This limits a range of three-dimensional data 837 to be transmitted, andthus reduces the data amount of three-dimensional data 837 to betransmitted.

Predetermined distance L varies in accordance with traveling speed V ofvehicle 801. For example, predetermined distance L is longer astraveling speed V is faster. This enables vehicle 801 to set anappropriate small space 802 in accordance with traveling speed V ofvehicle 801, and thus to transmit three-dimensional data 837 of suchsmall space 802 to a following vehicle, etc.

Also, the predetermined size varies in accordance with traveling speed Vof vehicle 801. For example, the predetermined size is greater astraveling speed V is faster. For example, depth D is greater, which isthe length of small space 802 in the traveling direction of the vehicle,as traveling speed V is faster. This enables vehicle 801 to set anappropriate small space 802 in accordance with traveling speed V ofvehicle 801, and thus to transmit three-dimensional data 837 of suchsmall space 802 to a following vehicle, etc.

Three-dimensional data creation device 810 judges whether a change hasoccurred in three-dimensional data 835 of small space 802 correspondingto three-dimensional data 837 already transmitted. When judging that achange has occurred, three-dimensional data creation device 810transmits, to a following vehicle, etc. outside, three-dimensional data837 (fourth three-dimensional data) that is at least part ofthree-dimensional data 835 in which the change has occurred.

This enables vehicle 801 to transmit, to a following vehicle, etc.,three-dimensional data 837 of the space in which a change has occurred.

Also, three-dimensional data creation device 810 more preferentiallytransmits three-dimensional data 837 (fourth three-dimensional data) inwhich a change has occurred than normal three-dimensional data 837(third three-dimensional data) that is transmitted at regular timeintervals. More specifically, three-dimensional data creation device 810transmits three-dimensional data 837 (fourth three-dimensional data) inwhich a change has occurred before transmitting normal three-dimensionaldata 837 (third three-dimensional data) that is transmitted at regulartime intervals. Stated differently, three-dimensional data creationdevice 810 transmits three-dimensional data 837 (fourththree-dimensional data) in which a change has occurred at irregular timeintervals without waiting for the transmission of normalthree-dimensional data 837 that is transmitted at regular timeintervals.

This enables vehicle 801 to preferentially transmit, to a followingvehicle, etc., three-dimensional data 837 of the space in which a changehas occurred, thereby enabling the following vehicle, etc., to promptlymake a judgment that is based on the three-dimensional data.

Three-dimensional data 837 (fourth three-dimensional data) in which thechange has occurred indicates a difference between three-dimensionaldata 835 of small space 802 corresponding to three-dimensional data 837already transmitted and three-dimensional data 835 that has undergonethe change. This reduces the data amount of three-dimensional data 837to be transmitted.

Three-dimensional data creation device 810 does not transmitthree-dimensional data 837 of small space 802, when no difference ispresent between three-dimensional data 837 of small space 802 andthree-dimensional data 831 of small space 802. Also, three-dimensionaldata creation device 810 may transmit, to the external device,information indicating that no difference is present betweenthree-dimensional data 837 of small space 802 and three-dimensional data831 of small space 802.

This prevents the transmission of unnecessary three-dimensional data837, thereby reducing the data amount of three-dimensional data 837 tobe transmitted.

Embodiment 6

In the present embodiment, a display device and a display method whichdisplay information obtained from a three-dimensional map, etc., and astoring device and storing method for storing a three-dimensional map,etc., will be described.

A mobile object such as a car or robot makes use of a three-dimensionalmap obtainable by communication with a server or another vehicle andtwo-dimensional video or self-detected three-dimensional data obtainablefrom a sensor equipped in the own vehicle, for the self-driving of thecar or the autonomous travelling of the robot. Among such data, it ispossible that data that the user wants to watch or store is differentdepending on conditions. Hereinafter, a display device that switchesdisplay according to the conditions will be described.

FIG. 41 is a flowchart showing an outline of a display method performedby the display device. The display device is equipped in a mobile objectsuch as a car or a robot. Note that an example in which the mobileobject is a vehicle (car) will be described below.

First, the display device determines which between two-dimensionalsurrounding information and three-dimensional surrounding information isto be displayed, according to the driving conditions of the vehicle(S901). Note that the two-dimensional surrounding informationcorresponds to the first surrounding information in the claims, and thethree-dimensional surrounding information corresponds to the secondsurrounding information in the claims Here, surrounding information isinformation indicating the surroundings of the mobile object, and is forexample, video of a view in a particular direction from the vehicle or amap of the surroundings of the vehicle.

Two-dimensional surrounding information is information generated usingtwo-dimensional data. Here, two-dimensional data is two-dimensional mapinformation or video. For example, two-dimensional surroundinginformation is a map of the vehicle's surroundings obtained from atwo-dimensional map or video obtained using a camera equipped in thevehicle. Furthermore, the two-dimensional surrounding information, forexample, does not include three-dimensional information. Specifically,when the two-dimensional surrounding information is a map of thevehicle's surroundings, the map does not include height directioninformation. Furthermore, when the two-dimensional surroundinginformation is video obtained using a camera, the video does not includedepth direction information.

Furthermore, the three-dimensional surrounding information isinformation generated using three-dimensional data. Here, thethree-dimensional data is, for example, a three-dimensional map. Notethat the three-dimensional data may be information, etc., indicating thethree-dimensional position or the three-dimensional shape of a target inthe vehicle's surroundings obtained from another vehicle or a server, ordetected by the own vehicle. For example, the three-dimensionalsurrounding information is a two-dimensional or three-dimensional videoor map of the vehicle's surroundings generated using a three-dimensionalmap. Furthermore, the three-dimensional surrounding information, forexample, includes three-dimensional information. For example, when thethree-dimensional surrounding information is a video of the view aheadof the vehicle, the video includes information indicating the distanceup to a target in the video. Furthermore, in the video, a pedestrian, orthe like, present ahead of a preceding vehicle is displayed.Furthermore, the three-dimensional surrounding information may beinformation in which information indicating the distance or thepedestrian, etc., is superimposed on video obtainable from a sensorequipped in the vehicle. Furthermore, the three-dimensional surroundinginformation may be information in which height direction information issuperimposed on a two-dimensional map.

Furthermore, the three-dimensional data may be three-dimensionallydisplayed, or a two-dimensional video or a two-dimensional map obtainedfrom three-dimensional data may be displayed on a two-dimensionaldisplay, or the like.

When it is determined in step S901 that three-dimensional surroundinginformation is to be displayed (Yes in S902), the display devicedisplays three-dimensional surrounding information (S903). On the otherhand, when it is determined in step S901 that two-dimensionalsurrounding information is to be displayed (No in S902), the displaydevice displays two-dimensional surrounding information (S904). In thismanner, the display device displays the three-dimensional surroundinginformation or the two-dimensional surrounding information that isdetermined to be displayed in step S901.

A specific example will be displayed below. In a first example, thedisplay device switches the surrounding information to be displayedaccording to whether the vehicle is under self-driving or manualdriving. Specifically, during self-driving, the driver does not need toknow in detail the detailed surrounding road information, and thus thedisplay device displays two-dimensional surrounding information (forexample, a two-dimensional map). On the other hand, during manualdriving, the display device displays three-dimensional surroundinginformation (for example, three-dimensional map) so that the driverknows the details of the road information of the surroundings for safedriving.

Furthermore, during self-driving, in order to indicate to the user thekind of information on which the driving of the own vehicle is based,the display device may display information that influenced the drivingoperation (for example, an SWLD used in self-location estimation,traffic lanes, road signs, surrounding condition detection results,etc.). For example, the display device may display such information inaddition to a two-dimensional map.

Note that the surrounding information to be displayed duringself-driving and manual driving described above is merely an example,and the display device may display three-dimensional surroundinginformation during self-driving and display two-dimensional surroundinginformation during manual driving. Furthermore, in at least one ofself-driving and manual driving, the display device may display metadataor a surrounding condition search result in addition to atwo-dimensional or three-dimensional map or video, or may displaymetadata or a surrounding condition search result in place of atwo-dimensional or three-dimensional map or video. Here, metadata isinformation indicating the three-dimensional position orthree-dimensional shape of a target obtained from a server or anothervehicle. Furthermore, the surrounding condition search result isinformation indicating the three-dimensional position orthree-dimensional shape of a target detected by the own vehicle.

In a second example, the display device switches the surroundinginformation to be displayed according to the operating environment. Forexample, the display device switches the surrounding information to bedisplayed according to the brightness outside. Specifically, when thesurroundings of the own vehicle are bright, the display device displaystwo-dimensional video obtainable using a camera equipped in the ownvehicle or three-dimensional surrounding information created using thetwo-dimensional video. On the other hand, when the surroundings of theown vehicle are dark, two-dimensional video obtainable from the cameraequipped in the own vehicle is dark and hard to watch, and thus thedisplay device displays three-dimensional surrounding informationcreated using LiDAR or millimeter wave radar.

Furthermore, the display device switches the surrounding information tobe displayed according to a driving area which is the area in which theown-vehicle is currently present. For example, in a tourist spot, a citycenter, or the vicinity of a target location, the display devicedisplays three-dimensional surrounding information to be able to providethe user with information of surrounding buildings, or the like. On theother hand, since there are many cases where detailed information of thesurroundings is considered unnecessary in a mountainous area or thesuburbs, etc., the display device displays two-dimensional surroundinginformation.

Furthermore, the display device may switch the surrounding informationto be displayed based on weather conditions. For example, in the case ofgood weather, the display device displays three-dimensional surroundinginformation created using the camera or LiDAR. On the other hand, in thecase of rain or dense fog, the three-dimensional surrounding informationobtainable from a camera or LiDAR tends to include noise, and thus thedisplay device displays three-dimensional surrounding informationcreated using millimeter wave radar.

Furthermore, these switching of displays may be carried outautomatically by a system or may be carried out manually by the user.

Furthermore, the three-dimensional surrounding information is generatedfrom any one or more of dense point cloud data generated based on a WLD,mesh data generated based on a MWLD, sparse data generated based on aSWLD, lane data generated based on a lane world, two-dimensional mapdata including three-dimensional shape information of roads andintersections, and metadata including three-dimensional position orthree-dimensional shape information that changes in real time or ownvehicle detection results.

Note that, as described above, a WLD is three-dimensional point clouddata, and a SWLD is data obtained by extracting a point cloud having anamount of a feature greater than or equal to a threshold. Furthermore, aMWLD is data having a mesh structure generated from a WLD. A lane worldis data obtained by extracting, from a WLD, a point cloud which has anamount of a feature greater than or equal to a threshold and is requiredfor self-location estimation, driving assist, self-driving, or the like.

Here, a MWLD and a SWLD have a smaller amount of data compared to a WLD.Therefore, by using a WLD when more detailed data is required, andotherwise using a MWLD or a SWLD, the communication data amount and theprocessing amount can be appropriately reduced. Furthermore, a laneworld has a smaller amount of data compared to a SWLD. Therefore, byusing a lane world, the communication data amount and the processingamount can be further reduced.

Furthermore, although an example of switching between two-dimensionalsurrounding information and three-dimensional surrounding data isdescribed above, the display device may switch the type of data (WLD,SWLD, etc.) to be used in generating three-dimensional surroundinginformation, based on the above-described conditions. Specifically, inthe foregoing description, the display device displays three-dimensionalsurrounding information generated from first data (for example, a WLD ora SWLD) having a larger amount of data in the case of displayingthree-dimensional surrounding information, and may displaythree-dimensional surrounding information generated from second data(for example, a SWLD or a lane world) having a smaller amount of datathan the first data instead of two-dimensional surrounding data in thecase of displaying two-dimensional surrounding data.

Furthermore, the display data displays the two-dimensional surroundingdata or the three-dimensional surrounding information on, for example, atwo-dimensional display equipped in the own vehicle, a head-up display,or a head-mounted display. Furthermore, the display device may transmitand display the two-dimensional surrounding data or thethree-dimensional surrounding information on a mobile terminal such as asmartphone by radio communication. Specifically, the display device isnot limited to being equipped in the mobile object, as long as it isequipped in a device that operates in conjunction with the mobileobject. For example, when the user carrying a display device such as asmartphone boards the mobile device or operates the mobile device,information on the mobile object such as the location of the mobileobject based on self-location detection of the mobile object isdisplayed on the display device, or such information together withsurrounding information is displayed on the display device.

Furthermore, when displaying a three-dimensional map, the display devicemay render the three-dimensional map and display it as two-dimensionaldata or may display the three-dimensional map as three-dimensional databy using a three-dimensional display or a three-dimensional hologram.

Next, a method of storing the three-dimensional map will be described. Amobile object such as a car or robot makes use of a three-dimensionalmap obtainable by communication with a server or another vehicle andtwo-dimensional video or self-detected three-dimensional data obtainablefrom a sensor equipped in the own vehicle, for the self-driving of thecar or the autonomous travelling of the robot. Among such data, datathat the user wants to watch or store is different depending onconditions. Hereinafter, a method of storing data according toconditions will be described.

The storing device is equipped in a mobile object such as a car or arobot. Note that an example in which the mobile object is a vehicle(car) will be described below. First, the storing device may be includedin the above-described display device.

In a first example, the storing device determines whether to store athree-dimensional map based on the area. Here, storing thethree-dimensional map in a recording medium of the own vehicle enablesself-driving inside the stored space without communication with theserver. However, since the memory capacity is limited, only limited datacan be stored. For this reason, the storing device limits the area to bestored in the manner indicated below.

For example, the storing device preferentially stores athree-dimensional map of an area frequently passed such as a commutationpath or the surroundings of the home. This eliminates the need to obtaindata of a frequently used area every time, and thus the communicationdata amount can be effectively reduced. Note that preferentially storerefers to storing data having higher priority within a predeterminedmemory capacity. For example, when new data cannot be stored within thememory capacity, data having lower priority than the new data isdeleted.

Alternatively, the storing device preferentially stores thethree-dimensional map of an area in which the communication environmentis poor. Accordingly, in an area in which the communication environmentis poor, the need to obtain data via communication is eliminated, thusthe occurrence of cases in which a three-dimensional map cannot beobtained due to poor communication can be reduced.

Alternatively, the storing device preferentially stores thethree-dimensional map of an area in which traffic volume is high.Accordingly, it is possible to preferentially store thethree-dimensional map of an area in which occurrence of accidents ishigh. Therefore, in which in such an area, the inability to obtain athree-dimensional map due to poor communication, and the deteriorationof precision of self-driving or driving assist can be reduced.

Alternatively, the storing device preferentially stores thethree-dimensional map of an area in which traffic volume is low. Here,in an area in which traffic volume is low, the possibility that aself-driving mode for automatically following the preceding vehiclecannot be used becomes high. With this, there are cases where moredetailed surrounding information becomes necessary. Therefore, bystoring the three-dimensional map of an area in which traffic volume islow, the precision of self-driving or driving assist in such an area canbe improved.

Note that the above-described storing methods may be combined.

Furthermore, these areas for which a three-dimensional map is to bepreferentially stored may be automatically determined by a system, ormay be specified by the user.

Furthermore, the storing device may delete, or updated with new data, athree-dimensional map for which a predetermined period has elapsed afterstoring. Accordingly, it is possible to prevent old map data from beingused. Furthermore, in updating map data, the storing device may updateonly an area in which there is a change by comparing an old map and anew map to detect a difference area which is a spatial area where thereis a difference, and adding the data of the difference area of the newmap to the old map or removing the data of the difference area from theold map.

Furthermore, in this example, the stored three-dimensional map is usedfor self-driving. Therefore, by using a SWLD for the three-dimensionalmap, the communication data amount can be reduced. Note that thethree-dimensional map is not limited to a SWLD, and may be another typeof data such as WLD, etc.

In a second example, the storing device stores a three-dimensional mapbased on an event.

For example, the storing device stores as a three-dimensional map aspecial event to be encountered while the vehicle is underway. Withthis, the user can subsequently view, etc., details of the event.Examples of events to be stored as a three-dimensional map are indicatedbelow. Note that the storing device may store three-dimensionalsurrounding information generated from a three-dimensional map.

For example, the storing device stores a three-dimensional map beforeand after a collision accident, or when danger is sensed, etc.

Alternatively, the storing device stores a three-dimensional map of acharacteristic scene such as beautiful scenery, a crowded place, or atourist spot. These events to be stored may be automatically determinedby a system or may be specified in advance by the user. For example, asa method of judging these events, machine learning may be used.

Furthermore, in this example, the stored three-dimensional map is usedfor viewing. Therefore, by using a WLD for the three-dimensional map,high-definition video can be provided. Note that the three-dimensionalmap is not limited to a WLD, and may be another type of data such asSWLD, etc.

Hereinafter, a method in which the display device controls displayaccording to the user will be described. When displaying the surroundingcondition detection result obtained by inter-vehicle communication bysuperimposing it on a map, the display device represents a nearbyvehicle using wireframe or represents a nearby vehicle with transparencyin order to make a detected object on a far side of the nearby vehiclevisible. Alternatively, the display device may display video from anoverhead perspective to enable a birds-eye view of the own vehicle, thenearby vehicle, and the surrounding condition detection result.

When the surrounding condition detection result or the point cloud datais superimposed on the surrounding environment visible through thewindshield, using a head-up display, as illustrated in FIG. 42, theposition at which information is to be superimposed may becomemisaligned due to a difference in the posture, physique, or eye positionof the user. FIG. 43 is a diagram illustrating an example of a displayon a head-up display when the superimposition position is misaligned.

In order to correct such a misalignment, the display device detects theposture, physique, or eye position of the user using information from avehicle interior camera or a sensor equipped in a vehicle seat. Thedisplay device adjusts the position at which information is to besuperimposed according to the posture, physique, or eye position of theuser detected. FIG. 44 is a diagram illustrating an example of thedisplay on the head-up display after adjustment.

Note that such a superimposition position adjustment may be performedmanually by the user using a control device equipped in the car.

Furthermore, during a disaster, the display device may indicate a safeplace on the map, and present this to the user. Alternatively, thevehicle may convey, to the user, details of the disaster and that factof going to a safe place, and perform self-driving up to the safe place.

For example, when an earthquake occurs, the vehicle may set an area witha high sea-level altitude as the destination to avoid getting caught upin a tsunami. At this time, the vehicle may obtain, throughcommunication with a server, information on roads that have becomedifficult to pass through due to the earthquake, and perform processingaccording to the details of the disaster such as taking a route thatavoids such roads.

Furthermore, the self-driving may include a plurality of modes such astravel mode, drive mode, etc.

In travel mode, the vehicle determines the route up to a destinationwith consideration being given to arrival time earliness, fee cheapness,travel distance shortness, energy consumption lowness, etc., andperforms self-driving according to the determined route.

In drive mode, the vehicle automatically determines the route so as toarrive at the destination at the time specified by the user. Forexample, when the user sets the destination and arrival time, thevehicle determines a route that enables the user to go around a nearbytourist spot and arrive at the destination at the set time.

Embodiment 7

In embodiment 5, an example is described in which a client device of avehicle or the like transmits three-dimensional data to another vehicleor a server such as a cloud-based traffic monitoring system. In thepresent embodiment, a client device transmits sensor informationobtained through a sensor to a server or a client device.

A structure of a system according to the present embodiment will firstbe described. FIG. 45 is a diagram showing the structure of atransmission/reception system of a three-dimensional map and sensorinformation according to the present embodiment. This system includesserver 901, and client devices 902A and 902B. Note that client devices902A and 902B are also referred to as client device 902 when noparticular distinction is made therebetween.

Client device 902 is, for example, a vehicle-mounted device equipped ina mobile object such as a vehicle. Server 901 is, for example, acloud-based traffic monitoring system, and is capable of communicatingwith the plurality of client devices 902.

Server 901 transmits the three-dimensional map formed by a point cloudto client device 902. Note that a structure of the three-dimensional mapis not limited to a point cloud, and may also be another structureexpressing three-dimensional data such as a mesh structure.

Client device 902 transmits the sensor information obtained by clientdevice 902 to server 901. The sensor information includes, for example,at least one of information obtained by LIDAR, a visible light image, aninfrared image, a depth image, sensor position information, or sensorspeed information.

The data to be transmitted and received between server 901 and clientdevice 902 may be compressed in order to reduce data volume, and mayalso be transmitted uncompressed in order to maintain data precision.When compressing the data, it is possible to use a three-dimensionalcompression method on the point cloud based on, for example, an octreestructure. It is possible to use a two-dimensional image compressionmethod on the visible light image, the infrared image, and the depthimage. The two-dimensional image compression method is, for example,MPEG-4 AVC or HEVC standardized by MPEG.

Server 901 transmits the three-dimensional map managed by server 901 toclient device 902 in response to a transmission request for thethree-dimensional map from client device 902. Note that server 901 mayalso transmit the three-dimensional map without waiting for thetransmission request for the three-dimensional map from client device902. For example, server 901 may broadcast the three-dimensional map toat least one client device 902 located in a predetermined space. Server901 may also transmit the three-dimensional map suited to a position ofclient device 902 at fixed time intervals to client device 902 that hasreceived the transmission request once. Server 901 may also transmit thethree-dimensional map managed by server 901 to client device 902 everytime the three-dimensional map is updated.

Client device 902 sends the transmission request for thethree-dimensional map to server 901. For example, when client device 902wants to perform the self-location estimation during traveling, clientdevice 902 transmits the transmission request for the three-dimensionalmap to server 901.

Note that in the following cases, client device 902 may send thetransmission request for the three-dimensional map to server 901. Clientdevice 902 may send the transmission request for the three-dimensionalmap to server 901 when the three-dimensional map stored by client device902 is old. For example, client device 902 may send the transmissionrequest for the three-dimensional map to server 901 when a fixed periodhas passed since the three-dimensional map is obtained by client device902.

Client device 902 may also send the transmission request for thethree-dimensional map to server 901 before a fixed time when clientdevice 902 exits a space shown in the three-dimensional map stored byclient device 902. For example, client device 902 may send thetransmission request for the three-dimensional map to server 901 whenclient device 902 is located within a predetermined distance from aboundary of the space shown in the three-dimensional map stored byclient device 902. When a movement path and a movement speed of clientdevice 902 are understood, a time when client device 902 exits the spaceshown in the three-dimensional map stored by client device 902 may bepredicted based on the movement path and the movement speed of clientdevice 902.

Client device 902 may also send the transmission request for thethree-dimensional map to server 901 when an error during alignment ofthe three-dimensional data and the three-dimensional map created fromthe sensor information by client device 902 is at least at a fixedlevel.

Client device 902 transmits the sensor information to server 901 inresponse to a transmission request for the sensor information fromserver 901. Note that client device 902 may transmit the sensorinformation to server 901 without waiting for the transmission requestfor the sensor information from server 901. For example, client device902 may periodically transmit the sensor information during a fixedperiod when client device 902 has received the transmission request forthe sensor information from server 901 once. Client device 902 maydetermine that there is a possibility of a change in thethree-dimensional map of a surrounding area of client device 902 havingoccurred, and transmit this information and the sensor information toserver 901, when the error during alignment of the three-dimensionaldata created by client device 902 based on the sensor information andthe three-dimensional map obtained from server 901 is at least at thefixed level.

Server 901 sends a transmission request for the sensor information toclient device 902. For example, server 901 receives positioninformation, such as GPS information, about client device 902 fromclient device 902. Server 901 sends the transmission request for thesensor information to client device 902 in order to generate a newthree-dimensional map, when it is determined that client device 902 isapproaching a space in which the three-dimensional map managed by server901 contains little information, based on the position information aboutclient device 902. Server 901 may also send the transmission request forthe sensor information, when wanting to (i) update the three-dimensionalmap, (ii) check road conditions during snowfall, a disaster, or thelike, or (iii) check traffic congestion conditions, accident/incidentconditions, or the like.

Client device 902 may set an amount of data of the sensor information tobe transmitted to server 901 in accordance with communication conditionsor bandwidth during reception of the transmission request for the sensorinformation to be received from server 901. Setting the amount of dataof the sensor information to be transmitted to server 901 is, forexample, increasing/reducing the data itself or appropriately selectinga compression method.

FIG. 46 is a block diagram showing an example structure of client device902. Client device 902 receives the three-dimensional map formed by apoint cloud and the like from server 901, and estimates a self-locationof client device 902 using the three-dimensional map created based onthe sensor information of client device 902. Client device 902 transmitsthe obtained sensor information to server 901.

Client device 902 includes data receiver 1011, communication unit 1012,reception controller 1013, format converter 1014, sensors 1015,three-dimensional data creator 1016, three-dimensional image processor1017, three-dimensional data storage 1018, format converter 1019,communication unit 1020, transmission controller 1021, and datatransmitter 1022.

Data receiver 1011 receives three-dimensional map 1031 from server 901.Three-dimensional map 1031 is data that includes a point cloud such as aWLD or a SWLD. Three-dimensional map 1031 may include compressed data oruncompressed data.

Communication unit 1012 communicates with server 901 and transmits adata transmission request (e.g. transmission request forthree-dimensional map) to server 901.

Reception controller 1013 exchanges information, such as information onsupported formats, with a communications partner via communication unit1012 to establish communication with the communications partner.

Format converter 1014 performs a format conversion and the like onthree-dimensional map 1031 received by data receiver 1011 to generatethree-dimensional map 1032. Format converter 1014 also performs adecompression or decoding process when three-dimensional map 1031 iscompressed or encoded. Note that format converter 1014 does not performthe decompression or decoding process when three-dimensional map 1031 isuncompressed data.

Sensors 815 are a group of sensors, such as LIDARs, visible lightcameras, infrared cameras, or depth sensors that obtain informationabout the outside of a vehicle equipped with client device 902, andgenerate sensor information 1033. Sensor information 1033 is, forexample, three-dimensional data such as a point cloud (point group data)when sensors 1015 are laser sensors such as LIDARs. Note that a singlesensor may serve as sensors 1015.

Three-dimensional data creator 1016 generates three-dimensional data1034 of a surrounding area of the own vehicle based on sensorinformation 1033. For example, three-dimensional data creator 1016generates point cloud data with color information on the surroundingarea of the own vehicle using information obtained by LIDAR and visiblelight video obtained by a visible light camera.

Three-dimensional image processor 1017 performs a self-locationestimation process and the like of the own vehicle, using (i) thereceived three-dimensional map 1032 such as a point cloud, and (ii)three-dimensional data 1034 of the surrounding area of the own vehiclegenerated using sensor information 1033. Note that three-dimensionalimage processor 1017 may generate three-dimensional data 1035 about thesurroundings of the own vehicle by merging three-dimensional map 1032and three-dimensional data 1034, and may perform the self-locationestimation process using the created three-dimensional data 1035.

Three-dimensional data storage 1018 stores three-dimensional map 1032,three-dimensional data 1034, three-dimensional data 1035, and the like.

Format converter 1019 generates sensor information 1037 by convertingsensor information 1033 to a format supported by a receiver end. Notethat format converter 1019 may reduce the amount of data by compressingor encoding sensor information 1037. Format converter 1019 may omit thisprocess when format conversion is not necessary. Format converter 1019may also control the amount of data to be transmitted in accordance witha specified transmission range.

Communication unit 1020 communicates with server 901 and receives a datatransmission request (transmission request for sensor information) andthe like from server 901.

Transmission controller 1021 exchanges information, such as informationon supported formats, with a communications partner via communicationunit 1020 to establish communication with the communications partner.

Data transmitter 1022 transmits sensor information 1037 to server 901.Sensor information 1037 includes, for example, information obtainedthrough sensors 1015, such as information obtained by LIDAR, a luminanceimage obtained by a visible light camera, an infrared image obtained byan infrared camera, a depth image obtained by a depth sensor, sensorposition information, and sensor speed information.

A structure of server 901 will be described next. FIG. 47 is a blockdiagram showing an example structure of server 901. Server 901 transmitssensor information from client device 902 and creates three-dimensionaldata based on the received sensor information. Server 901 updates thethree-dimensional map managed by server 901 using the createdthree-dimensional data. Server 901 transmits the updatedthree-dimensional map to client device 902 in response to a transmissionrequest for the three-dimensional map from client device 902.

Server 901 includes data receiver 1111, communication unit 1112,reception controller 1113, format converter 1114, three-dimensional datacreator 1116, three-dimensional data merger 1117, three-dimensional datastorage 1118, format converter 1119, communication unit 1120,transmission controller 1121, and data transmitter 1122.

Data receiver 1111 receives sensor information 1037 from client device902. Sensor information 1037 includes, for example, information obtainedby LIDAR, a luminance image obtained by a visible light camera, aninfrared image obtained by an infrared camera, a depth image obtained bya depth sensor, sensor position information, sensor speed information,and the like.

Communication unit 1112 communicates with client device 902 andtransmits a data transmission request (e.g. transmission request forsensor information) and the like to client device 902.

Reception controller 1113 exchanges information, such as information onsupported formats, with a communications partner via communication unit1112 to establish communication with the communications partner.

Format converter 1114 generates sensor information 1132 by performing adecompression or decoding process when the received sensor information1037 is compressed or encoded. Note that format converter 1114 does notperform the decompression or decoding process when sensor information1037 is uncompressed data.

Three-dimensional data creator 1116 generates three-dimensional data1134 of a surrounding area of client device 902 based on sensorinformation 1132. For example, three-dimensional data creator 1116generates point cloud data with color information on the surroundingarea of client device 902 using information obtained by LIDAR andvisible light video obtained by a visible light camera.

Three-dimensional data merger 1117 updates three-dimensional map 1135 bymerging three-dimensional data 1134 created based on sensor information1132 with three-dimensional map 1135 managed by server 901.

Three-dimensional data storage 1118 stores three-dimensional map 1135and the like.

Format converter 1119 generates three-dimensional map 1031 by convertingthree-dimensional map 1135 to a format supported by the receiver end.Note that format converter 1119 may reduce the amount of data bycompressing or encoding three-dimensional map 1135. Format converter1119 may omit this process when format conversion is not necessary.Format converter 1119 may also control the amount of data to betransmitted in accordance with a specified transmission range.

Communication unit 1120 communicates with client device 902 and receivesa data transmission request (transmission request for three-dimensionalmap) and the like from client device 902.

Transmission controller 1121 exchanges information, such as informationon supported formats, with a communications partner via communicationunit 1120 to establish communication with the communications partner.

Data transmitter 1122 transmits three-dimensional map 1031 to clientdevice 902. Three-dimensional map 1031 is data that includes a pointcloud such as a WLD or a SWLD. Three-dimensional map 1031 may includeone of compressed data and uncompressed data.

An operational flow of client device 902 will be described next. FIG. 48is a flowchart of an operation when client device 902 obtains thethree-dimensional map.

Client device 902 first requests server 901 to transmit thethree-dimensional map (point cloud, etc.) (S1001). At this point, byalso transmitting the position information about client device 902obtained through GPS and the like, client device 902 may also requestserver 901 to transmit a three-dimensional map relating to this positioninformation.

Client device 902 next receives the three-dimensional map from server901 (S1002). When the received three-dimensional map is compressed data,client device 902 decodes the received three-dimensional map andgenerates an uncompressed three-dimensional map (S1003).

Client device 902 next creates three-dimensional data 1034 of thesurrounding area of client device 902 using sensor information 1033obtained by sensors 1015 (S1004). Client device 902 next estimates theself-location of client device 902 using three-dimensional map 1032received from server 901 and three-dimensional data 1034 created usingsensor information 1033 (S1005).

FIG. 49 is a flowchart of an operation when client device 902 transmitsthe sensor information. Client device 902 first receives a transmissionrequest for the sensor information from server 901 (S1011). Clientdevice 902 that has received the transmission request transmits sensorinformation 1037 to server 901 (S1012). Note that client device 902 maygenerate sensor information 1037 by compressing each piece ofinformation using a compression method suited to each piece ofinformation, when sensor information 1033 includes a plurality of piecesof information obtained by sensors 1015.

An operational flow of server 901 will be described next. FIG. 50 is aflowchart of an operation when server 901 obtains the sensorinformation. Server 901 first requests client device 902 to transmit thesensor information (S1021). Server 901 next receives sensor information1037 transmitted from client device 902 in accordance with the request(S1022). Server 901 next creates three-dimensional data 1134 using thereceived sensor information 1037 (S1023). Server 901 next reflects thecreated three-dimensional data 1134 in three-dimensional map 1135(S1024).

FIG. 51 is a flowchart of an operation when server 901 transmits thethree-dimensional map. Server 901 first receives a transmission requestfor the three-dimensional map from client device 902 (S1031). Server 901that has received the transmission request for the three-dimensional maptransmits the three-dimensional map to client device 902 (S1032). Atthis point, server 901 may extract a three-dimensional map of a vicinityof client device 902 along with the position information about clientdevice 902, and transmit the extracted three-dimensional map. Server 901may compress the three-dimensional map formed by a point cloud using,for example, an octree structure compression method, and transmit thecompressed three-dimensional map.

Hereinafter, variations of the present embodiment will be described.Server 901 creates three-dimensional data 1134 of a vicinity of aposition of client device 902 using sensor information 1037 receivedfrom client device 902. Server 901 next calculates a difference betweenthree-dimensional data 1134 and three-dimensional map 1135, by matchingthe created three-dimensional data 1134 with three-dimensional map 1135of the same area managed by server 901. Server 901 determines that atype of anomaly has occurred in the surrounding area of client device902, when the difference is greater than or equal to a predeterminedthreshold. For example, it is conceivable that a large difference occursbetween three-dimensional map 1135 managed by server 901 andthree-dimensional data 1134 created based on sensor information 1037,when land subsidence and the like occurs due to a natural disaster suchas an earthquake.

Sensor information 1037 may include information indicating at least oneof a sensor type, a sensor performance, and a sensor model number.Sensor information 1037 may also be appended with a class ID and thelike in accordance with the sensor performance. For example, when sensorinformation 1037 is obtained by LIDAR, it is conceivable to assignidentifiers to the sensor performance. A sensor capable of obtaininginformation with precision in units of several millimeters is class 1, asensor capable of obtaining information with precision in units ofseveral centimeters is class 2, and a sensor capable of obtaininginformation with precision in units of several meters is class 3. Server901 may estimate sensor performance information and the like from amodel number of client device 902. For example, when client device 902is equipped in a vehicle, server 901 may determine sensor specificationinformation from a type of the vehicle. In this case, server 901 mayobtain information on the type of the vehicle in advance, and theinformation may also be included in the sensor information. Server 901may change a degree of correction with respect to three-dimensional data1134 created using sensor information 1037, using the obtained sensorinformation 1037. For example, when the sensor performance is high inprecision (class 1), server 901 does not correct three-dimensional data1134. When the sensor performance is low in precision (class 3), server901 corrects three-dimensional data 1134 in accordance with theprecision of the sensor. For example, server 901 increases the degree(intensity) of correction with a decrease in the precision of thesensor.

Server 901 may simultaneously send the transmission request for thesensor information to the plurality of client devices 902 in a certainspace. Server 901 does not need to use all of the sensor information forcreating three-dimensional data 1134 and may, for example, select sensorinformation to be used in accordance with the sensor performance, whenhaving received a plurality of pieces of sensor information from theplurality of client devices 902. For example, when updatingthree-dimensional map 1135, server 901 may select high-precision sensorinformation (class 1) from among the received plurality of pieces ofsensor information, and create three-dimensional data 1134 using theselected sensor information.

Server 901 is not limited to only being a server such as a cloud-basedtraffic monitoring system, and may also be another (vehicle-mounted)client device. FIG. 52 is a diagram of a system structure in this case.

For example, client device 902C sends a transmission request for sensorinformation to client device 902A located nearby, and obtains the sensorinformation from client device 902A. Client device 902C then createsthree-dimensional data using the obtained sensor information of clientdevice 902A, and updates a three-dimensional map of client device 902C.This enables client device 902C to generate a three-dimensional map of aspace that can be obtained from client device 902A, and fully utilizethe performance of client device 902C. For example, such a case isconceivable when client device 902C has high performance.

In this case, client device 902A that has provided the sensorinformation is given rights to obtain the high-precisionthree-dimensional map generated by client device 902C. Client device902A receives the high-precision three-dimensional map from clientdevice 902C in accordance with these rights.

Server 901 may send the transmission request for the sensor informationto the plurality of client devices 902 (client device 902A and clientdevice 902B) located nearby client device 902C. When a sensor of clientdevice 902A or client device 902B has high performance, client device902C is capable of creating the three-dimensional data using the sensorinformation obtained by this high-performance sensor.

FIG. 53 is a block diagram showing a functionality structure of server901 and client device 902. Server 901 includes, for example,three-dimensional map compression/decoding processor 1201 thatcompresses and decodes the three-dimensional map and sensor informationcompression/decoding processor 1202 that compresses and decodes thesensor information.

Client device 902 includes three-dimensional map decoding processor 1211and sensor information compression processor 1212. Three-dimensional mapdecoding processor 1211 receives encoded data of the compressedthree-dimensional map, decodes the encoded data, and obtains thethree-dimensional map. Sensor information compression processor 1212compresses the sensor information itself instead of thethree-dimensional data created using the obtained sensor information,and transmits the encoded data of the compressed sensor information toserver 901. With this structure, client device 902 does not need tointernally store a processor that performs a process for compressing thethree-dimensional data of the three-dimensional map (point cloud, etc.),as long as client device 902 internally stores a processor that performsa process for decoding the three-dimensional map (point cloud, etc.).This makes it possible to limit costs, power consumption, and the likeof client device 902.

As stated above, client device 902 according to the present embodimentis equipped in the mobile object, and creates three-dimensional data1034 of a surrounding area of the mobile object using sensor information1033 that is obtained through sensor 1015 equipped in the mobile objectand indicates a surrounding condition of the mobile object. Clientdevice 902 estimates a self-location of the mobile object using thecreated three-dimensional data 1034. Client device 902 transmits theobtained sensor information 1033 to server 901 or another mobile object.

This enables client device 902 to transmit sensor information 1033 toserver 901 or the like. This makes it possible to further reduce theamount of transmission data compared to when transmitting thethree-dimensional data. Since there is no need for client device 902 toperform processes such as compressing or encoding the three-dimensionaldata, it is possible to reduce the processing amount of client device902. As such, client device 902 is capable of reducing the amount ofdata to be transmitted or simplifying the structure of the device.

Client device 902 further transmits the transmission request for thethree-dimensional map to server 901 and receives three-dimensional map1031 from server 901. In the estimating of the self-location, clientdevice 902 estimates the self-location using three-dimensional data 1034and three-dimensional map 1032.

Sensor information 1034 includes at least one of information obtained bya laser sensor, a luminance image, an infrared image, a depth image,sensor position information, or sensor speed information.

Sensor information 1033 includes information that indicates aperformance of the sensor.

Client device 902 encodes or compresses sensor information 1033, and inthe transmitting of the sensor information, transmits sensor information1037 that has been encoded or compressed to server 901 or another mobileobject 902. This enables client device 902 to reduce the amount of datato be transmitted.

For example, client device 902 includes a processor and memory. Theprocessor performs the above processes using the memory.

Server 901 according to the present embodiment is capable ofcommunicating with client device 902 equipped in the mobile object, andreceives sensor information 1037 that is obtained through sensor 1015equipped in the mobile object and indicates a surrounding condition ofthe mobile object. Server 901 creates three-dimensional data 1134 of asurrounding area of the mobile object using the received sensorinformation 1037.

With this, server 901 creates three-dimensional data 1134 using sensorinformation 1037 transmitted from client device 902. This makes itpossible to further reduce the amount of transmission data compared towhen client device 902 transmits the three-dimensional data. Since thereis no need for client device 902 to perform processes such ascompressing or encoding the three-dimensional data, it is possible toreduce the processing amount of client device 902. As such, server 901is capable of reducing the amount of data to be transmitted orsimplifying the structure of the device.

Server 901 further transmits a transmission request for the sensorinformation to client device 902.

Server 901 further updates three-dimensional map 1135 using the createdthree-dimensional data 1134, and transmits three-dimensional map 1135 toclient device 902 in in response to the transmission request forthree-dimensional map 1135 from client device 902.

Sensor information 1037 includes at least one of information obtained bya laser sensor, a luminance image, an infrared image, a depth image,sensor position information, or sensor speed information.

Sensor information 1037 includes information that indicates aperformance of the sensor.

Server 901 further corrects the three-dimensional data in accordancewith the performance of the sensor. This enables the three-dimensionaldata creation method to improve the quality of the three-dimensionaldata.

In the receiving of the sensor information, server 901 receives aplurality of pieces of sensor information 1037 received from a pluralityof client devices 902, and selects sensor information 1037 to be used inthe creating of three-dimensional data 1134, based on a plurality ofpieces of information that each indicates the performance of the sensorincluded in the plurality of pieces of sensor information 1037. Thisenables server 901 to improve the quality of three-dimensional data1134.

Server 901 decodes or decompresses the received sensor information 1037,and creates three-dimensional data 1134 using sensor information 1132that has been decoded or decompressed. This enables server 901 to reducethe amount of data to be transmitted.

For example, server 901 includes a processor and memory. The processorperforms the above processes using the memory.

A server, a client device, and the like according to the embodiments ofthe present disclosure have been described above, but the presentdisclosure is not limited to these embodiments.

Note that each of the processors included in the server, the clientdevice, and the like according to the above embodiments is typicallyimplemented as a large-scale integrated (LSI) circuit, which is anintegrated circuit (IC). These may take the form of individual chips, ormay be partially or entirely packaged into a single chip.

Such IC is not limited to an LSI, and thus may be implemented as adedicated circuit or a general-purpose processor. Alternatively, a fieldprogrammable gate array (FPGA) that allows for programming after themanufacture of an LSI, or a reconfigurable processor that allows forreconfiguration of the connection and the setting of circuit cellsinside an LSI may be employed.

Moreover, in the above embodiments, the structural components may beimplemented as dedicated hardware or may be realized by executing asoftware program suited to such structural components. Alternatively,the structural components may be implemented by a program executor suchas a CPU or a processor reading out and executing the software programrecorded in a recording medium such as a hard disk or a semiconductormemory.

The present disclosure may also be implemented as a three-dimensionaldata creation method and the like executed by the server, the clientdevice, and the like.

Also, the divisions of the functional blocks shown in the block diagramsare mere examples, and thus a plurality of functional blocks may beimplemented as a single functional block, or a single functional blockmay be divided into a plurality of functional blocks, or one or morefunctions may be moved to another functional block. Also, the functionsof a plurality of functional blocks having similar functions may beprocessed by single hardware or software in a parallelized ortime-divided manner.

Also, the processing order of executing the steps shown in theflowcharts is a mere illustration for specifically describing thepresent disclosure, and thus may be an order other than the shown order.Also, one or more of the steps may be executed simultaneously (inparallel) with another step.

A server, a client device, and the like according to one or more aspectshave been described above based on the embodiments, but the presentdisclosure is not limited to these embodiments. The one or more aspectsmay thus include forms achieved by making various modifications to theabove embodiments that can be conceived by those skilled in the art, aswell forms achieved by combining structural components in differentembodiments, without materially departing from the spirit of the presentdisclosure.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to a client device for creatingthree-dimensional data and a server.

What is claimed is:
 1. A three-dimensional data creation method in aclient device, the three-dimensional data creation method comprising:creating three-dimensional data of a surrounding area of the clientdevice using sensor information that is obtained through a sensorequipped in the client device and indicates a surrounding condition ofthe client device; estimating a self-location of the client device usingthe three-dimensional data created; and transmitting the sensorinformation obtained to a server or an other client device.
 2. Thethree-dimensional data creation method according to claim 1, furthercomprising: transmitting a transmission request for a three-dimensionalmap to the server; and receiving the three-dimensional map from theserver, wherein in the estimating of the self-location, theself-location is estimated using the three-dimensional data and thethree-dimensional map.
 3. The three-dimensional data creation methodaccording to claim 1, wherein the sensor information includes at leastone of information obtained by a laser sensor, a luminance image, aninfrared image, a depth image, sensor position information, or sensorspeed information.
 4. The three-dimensional data creation methodaccording to claim 1, wherein the sensor information includesinformation that indicates a performance of the sensor.
 5. Thethree-dimensional data creation method according to claim 1, furthercomprising: encoding or compressing the sensor information, wherein inthe transmitting of the sensor information, the sensor information thathas been encoded or compressed is transmitted to the server or the otherclient device.
 6. A three-dimensional data creation method in a serverthat is capable of communicating with a client device, thethree-dimensional data creation method comprising: receiving sensorinformation from the client device that is obtained through a sensorequipped in the client device and indicates a surrounding condition ofthe client device; and creating three-dimensional data of a surroundingarea of the client device using the sensor information received.
 7. Thethree-dimensional data creation method according to claim 6, furthercomprising: transmitting a transmission request for the sensorinformation to the client device.
 8. The three-dimensional data creationmethod according to claim 6, further comprising: updating athree-dimensional map using the three-dimensional data created; andtransmitting the three-dimensional map to the client device in responseto a transmission request for the three-dimensional map from the clientdevice.
 9. The three-dimensional data creation method according to claim6, wherein the sensor information includes at least one of informationobtained by a laser sensor, a luminance image, an infrared image, adepth image, sensor position information, or sensor speed information.10. The three-dimensional data creation method according to claim 6,wherein the sensor information includes information that indicates aperformance of the sensor.
 11. The three-dimensional data creationmethod according to claim 10, further comprising: correcting thethree-dimensional data in accordance with the performance of the sensor.12. The three-dimensional data creation method according to claim 10,wherein in the receiving of the sensor information: a plurality ofpieces of the sensor information are received from a plurality of clientdevices each being the client device; and the sensor information to beused in the creating of the three-dimensional data is selected, based ona plurality of pieces of information that each indicates the performanceof the sensor included in the plurality of pieces of the sensorinformation.
 13. The three-dimensional data creation method according toclaim 6, further comprising: decoding or decompressing the sensorinformation received; and creating the three-dimensional data using thesensor information that has been decoded or decompressed.
 14. A clientdevice, the client device comprising: a processor; and memory, whereinthe processor uses the memory to: create three-dimensional data of asurrounding area of the client device using sensor information that isobtained through a sensor equipped in the client device and indicates asurrounding condition of the client device; estimate a self-location ofthe client device using the three-dimensional data created; and transmitthe sensor information obtained to a server or an other client device.15. A server that is capable of communicating with a client device, theserver comprising: a processor; and memory, wherein the processor usesthe memory to: receive sensor information from the client device that isobtained through a sensor equipped in the client device and indicates asurrounding condition of the client device; and create three-dimensionaldata of a surrounding area of the client device using the sensorinformation received.